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"title": "Comparison of the Different Project Management Software used for a Commercial Project in the Philippines: A Case Study",
"normalizedTitle": "Comparison of the Different Project Management Software used for a Commercial Project in the Philippines: A Case Study",
"abstract": "In the Philippines, many industries have progressed during the past decade. The construction industry is one of these flourishing industries that has contributed to the country's social and economic development. Several factors affect the success of construction projects and most explored among them are the different systems for proper budget allocation and efficient scheduling. Project Management Information Systems (PMIS) specifically Project Management Software (PMS) have been studied and utilized in the industry to provide management teams with possible strategies and a general overall look at the current status, budget allocation, and scheduling while at the same time having a domain on the quality control of their projects. This paper aims to compare the different PMS (Primavera P6, MS Project, ProjectLibre, and MS Excel) in terms of Project Scheduling capability and outputs for the construction of a commercial establishment in Metro Manila, Philippines. Results of the comparative analysis show that Primavera P6 and MS Project both can produce the Work Breakdown Structure (WBS), Gantt Chart, Critical Path, and S-Curve since it is incorporated in the program but both software also have limited accessibility due to subscription requirement. Moreover, Primavera and MS Project require familiarity in using the software to maximize its functions. ProjectLibre being an open-source software that is free for download and use can also produce WBS, Gantt Chart, and S-Curve but through derivation and programming since it is not readily available. Microsoft Excel on the other hand can also produce the same outputs but requires a higher level and laborious programming. These findings can help project managers decide on the PMS suitable for their projects for an overall view of the progress from planning to implementation in order to assure its success.",
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"affiliation": "Dept. of Comput. Sci., Mississippi State Univ., MS, USA",
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"abstract": "An in-depth understanding of the failure features of HPC jobs in a supercomputer is critical to the large-scale system maintenance and improvement of the service quality for users. In this paper, we investigate the features of hundreds of thousands of jobs in one of the most powerful supercomputers, the IBM Blue Gene/Q Mira, based on 2001 days of observations with a total of over 32.44 billion core-hours. We study the impact of the system's events on the jobs' execution in order to understand the system's reliability from the perspective of jobs and users. The characterization involves a joint analysis based on multiple data sources, including the reliability, availability, and serviceability (RAS) log; job scheduling log; the log regarding each job's physical execution tasks; and the I/O behavior log. We present 22 valuable takeaways based on our in-depth analysis. For instance, 99,245 job failures are reported in the job-scheduling log, a large majority (99.4%) of which are due to user behavior (such as bugs in code, wrong configuration, or misoperations). The job failures are correlated with multiple metrics and attributes, such as users/projects and job execution structure (number of tasks, scale, and core-hours). The best-fitting distributions of a failed job's execution length (or interruption interval) include Weibull, Pareto, inverse Gaussian, and Erlang/exponential, depending on the types of errors (i.e., exit codes). The RAS events affecting job executions exhibit a high correlation with users and core-hours and have a strong locality feature. In terms of the failed jobs, our similarity-based event-filtering analysis indicates that the mean time to interruption is about 3.5 days.",
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"abstract": "The advent of non von Neumann computational models, specifically neuromorphic architectures, has engendered a new class of challenges for computer architects. On the one hand, each neuron-like computational element must consume minimal power and area to enable scaling up to biological scales of billions of neurons; this rules out direct support for complex and expensive features like floating point and transcendental functions. On the other hand, to fully benefit from cortical properties and operations, neuromorphic architectures must support complex non-linear neuronal behaviors. This semantic gap between the simple and power-efficient processing elements and complex neuronal behaviors has rekindled a RISC vs. CISC-like debate within the neuromorphic hardware design community. In this paper, we address the aforementioned semantic gap for a recently-described digital neuromorphic architecture that constitutes simple Linear-Leak Integrate-and-Fire (LLIF) spiking neurons as processing primitives. We show that despite the simplicity of LLIF primitives, a broad class of complex neuronal behaviors can be emulated by composing assemblies of such primitives with low area and power overheads. Furthermore, we demonstrate that for the LLIF primitives without built-in mechanisms for synaptic plasticity, two well-known neural learning rules-spike timing dependent plasticity and Hebbian learning-can be emulated via assemblies of LLIF primitives. By bridging the semantic gap for one such system we enable neuromorphic system developers, in general, to keep their hardware design simple and power-efficient and at the same time enjoy the benefits of complex neuronal behaviors essential for robust and accurate cortical simulation.",
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"abstract": "Neuronal connectivity graphs can give valuable insight into the structure of the brain and patterns of functional activity. In this paper we describe a connectivity visualization technique using contrasting styles to emphasize the differences between pairs of graphs. Our proposed technique enables interactive exploration of connectivity graphs at the various levels of the hierarchical structure of the brain — atlas regions, brain lobes and cerebral hemispheres. We demonstrate our methods on data obtained from matched pairs of subjects in a Parkinson's disease (PD) study. Control group data is displayed in a smooth, organic style with continuous transitions between views at different levels of the brain hierarchy using edge bundling and a new node bundling technique. Data from the PD group is displayed with glitch and noise effects inspired by PD symptoms, highlighting the differences between each subject and their matched pair from the control group. We conclude by describing avenues for further evaluation of this preliminary work.",
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"abstract": "Nanoscale technologies have gone from being just an ambitious concept to being a rapidly advancing area of interdisciplinary science with immense practical importance. Feynman's vision on nanoscience provided great impetus to the development of nanophysics, nanochemistry, nanoelectronics and nanotechnology in general. High resolution microscopic devices such as scanning tunneling microscope, transmission electron microscope and atomic force microscope etc. in mid 1980s allowed researchers to see individual atoms on surfaces and arrange them. The authors (nanobiologists, computer scientists, biotechnologists and material scientists) attempt to provide a review of the state of the art in the field of nanoscale technologies and its impact on various fields of research like computation, basic biology, medicine and agricultural biotechnology. Imprints of memory mechanisms in living systems operating at different levels (e.g. biochemical, immunological and neuronal) have provided inputs to design and fabricate 'bio-inspired' nanoelectronic devices suitable for various applications. Several examples of such nanoscale technology based frameworks and devices are presented in the scenario of their potential role in the development of future nanoscale technologies. Nanoscale technologies might finally revolutionize computational intelligence and thinking. The power and limits of computing processes govern the intelligence, knowledge acquisition and thinking process of human and machine. Present computational methods and models provide us courage to study the problem, but these tools are not yet sufficient to answer the following riddles of machine intelligence - what can computers do better than humans? What can humans do better than computers? And the most important one - what is computable? The authors try to present evidences that show bio-inspired nanoscale technologies might gain the power in helping us to go deeper into these challenges of research in future",
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"content": "Nanoscale technologies have gone from being just an ambitious concept to being a rapidly advancing area of interdisciplinary science with immense practical importance. Feynman's vision on nanoscience provided great impetus to the development of nanophysics, nanochemistry, nanoelectronics and nanotechnology in general. High resolution microscopic devices such as scanning tunneling microscope, transmission electron microscope and atomic force microscope etc. in mid 1980s allowed researchers to see individual atoms on surfaces and arrange them. The authors (nanobiologists, computer scientists, biotechnologists and material scientists) attempt to provide a review of the state of the art in the field of nanoscale technologies and its impact on various fields of research like computation, basic biology, medicine and agricultural biotechnology. Imprints of memory mechanisms in living systems operating at different levels (e.g. biochemical, immunological and neuronal) have provided inputs to design and fabricate 'bio-inspired' nanoelectronic devices suitable for various applications. Several examples of such nanoscale technology based frameworks and devices are presented in the scenario of their potential role in the development of future nanoscale technologies. Nanoscale technologies might finally revolutionize computational intelligence and thinking. The power and limits of computing processes govern the intelligence, knowledge acquisition and thinking process of human and machine. Present computational methods and models provide us courage to study the problem, but these tools are not yet sufficient to answer the following riddles of machine intelligence - what can computers do better than humans? What can humans do better than computers? And the most important one - what is computable? The authors try to present evidences that show bio-inspired nanoscale technologies might gain the power in helping us to go deeper into these challenges of research in future",
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"Agriculture",
"Biology Computing",
"Diseases",
"Learning Artificial Intelligence",
"Medical Image Processing",
"Molecular Biophysics",
"Nanobiotechnology",
"Nanoscale Technology",
"Agricultural Biotechnology",
"Biology Computing",
"Medicine",
"Scanning Tunneling Microscope",
"Transmission Electron Microscope",
"Atomic Force Microscope",
"Bio Inspired Nanoelectronic Devices",
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"Machine Intelligence",
"Biology Computing",
"Nanobioscience",
"Biotechnology",
"Atomic Force Microscopy",
"Scanning Electron Microscopy",
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"Humans",
"Nanoelectronics",
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"Agriculture",
"Alzheimers Disease",
"Biotechnology",
"Cancer",
"Computational Biology",
"Consciousness",
"Cybernetics",
"Genomics",
"HIV",
"Hydrophobic Nanosilica",
"Lipophilic Nanosilica",
"Machine Learning",
"Malaria",
"Metabolomics",
"Nanoscience",
"Nanosilica",
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"Quantum Mechanics",
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"affiliation": "Indian Statistical Institute, India; ICSIT, India",
"fullName": "D. Dutta Majumder",
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"affiliation": "Indian Statistical Institute, India",
"fullName": "R.L. Brahmachary",
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"affiliation": "Central Glass & Ceramic Research Institute, India",
"fullName": "Rajat Banerjee",
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"fullName": "Sumistha Das",
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"affiliation": "West Bengal University of Technology, India",
"fullName": "Indrani Roy",
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"affiliation": "ICSIT, India",
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"fullName": "Prity Sagar",
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"affiliation": "Humboldt University Berlin, Germany",
"fullName": "Carsten Schulz",
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"affiliation": "Hue University of Agriculture and Forestry, Vietnam",
"fullName": "Nguyen Quang Linh",
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"affiliation": "ISI, India",
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"abstract": "Large-scale numerical simulations of high-intensity focused ultrasound (HIFU), important for model-based treatment planning, generate large amounts of data. Typically, it is necessary to save hundreds of gigabytes during simulation. We propose a novel algorithm for time varying simulation data compression specialized for HIFU. Our approach is especially focused on the on-the-fly parallel data compression during simulations. Now, we are able to compress 3D pressure time series of linear and nonlinear simulations with very acceptable compression ratios and errors (over 80 % of the space can be saved with an acceptable error). The proposed compression will be helpful for significant reduction of resources, such as storage space, network bandwidth, CPU time, etc., enabling better treatment planning using fast volume data visualizations. The paper describes the proposed method, its experimental evaluation, and comparison to the state of the art.",
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"content": "Large-scale numerical simulations of high-intensity focused ultrasound (HIFU), important for model-based treatment planning, generate large amounts of data. Typically, it is necessary to save hundreds of gigabytes during simulation. We propose a novel algorithm for time varying simulation data compression specialized for HIFU. Our approach is especially focused on the on-the-fly parallel data compression during simulations. Now, we are able to compress 3D pressure time series of linear and nonlinear simulations with very acceptable compression ratios and errors (over 80 % of the space can be saved with an acceptable error). The proposed compression will be helpful for significant reduction of resources, such as storage space, network bandwidth, CPU time, etc., enabling better treatment planning using fast volume data visualizations. The paper describes the proposed method, its experimental evaluation, and comparison to the state of the art.",
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"affiliation": "Department of Computer Graphics and Multimedia, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic",
"fullName": "Petr Kleparnik",
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"affiliation": "Department of Computer Graphics and Multimedia, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic",
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"affiliation": "Department of Computer Systems, Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic",
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"title": "Development of Pseudo 3D Visualization System by Superimposing Ultrasound Images",
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"abstract": "This paper presents the development of pseudo 3D visualization system of organs using 2D ultrasound images for a new medical instrument. The new instrument consists of an ultrasonic endoscope and an electro-magnetic measurement sensor. The pseudo 3D volume is reconstructed by superimposing ultrasound images captured by the ultrasonic endoscope. So the new instrument shows not only the surface of organs, but also the 3D volume of inside of organs. However, it was reported that the ultrasound probe influenced the accuracy of the sensors, so it is necessary to investigate the influence of the ultrasound endoscope to the sensor. In this paper, we propose a 3D volume reconstruction system using 2D ultrasound images, and show experimental results of accuracy measurement experiments of two kinds of electro-magnetic measurement sensors and 3D visualization with actual ultrasound images.",
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"abstract": "Scene graph generation is widely studied in recent years, which tries to understand the interactions of different objects as a whole. The earlier researches only recognize a few relationships or model contexts among different relationships, neglecting the associations of predicates for each object pair. In this paper, we propose a two-stage framework named predicate association network (PANet) to properly extract contexts and model predicate association. In the first stage, instance-level and scene-level context are extracted for object classification and further used for predicate classification in the next stage. With a recurrent neural network, alignment technique and attention mechanism are combined to collect the associations of predicates in the second stage. The experiments on the Visual Genome dataset show that our method is effective and outperforms the state-of-the-art methods.",
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"content": "Medical ultrasound images are inherently corrupted with speckle noise in a multiplicative manner. The most popular approach of despeckling is homomorphic filtering, in which the multiplicative speckle noise converted to an additive one by log-transformation. The knowledge of the statistics of the log-transformed speckle is necessary for developing effective methods for speckle reduction. The Bessel K-Form (BKF) probability density function (pdf) is proposed to model the logarithmically transformed speckle noise in the dual-tree complex wavelet transform (DT-CWT) domain. A maximum likelihood based method is developed for estimating the parameters of the BKF pdf. The suitability of the BKF pdf in modeling the speckle is studied for different noise levels in the 2D DT-CWT domain. It is shown that the BKF can capture the statistics of the DT-CWT coefficients corresponding to log-transformed speckle better than the Gaussian and normal inverse Gaussian pdfs.",
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"abstract": "The first stage of a complete automatic handwritten signature verification system (AHSVS) is described in this paper. Since only random forgeries are taken into account in this first stage of decision, the directional probability density function (PDF) which is related to the overall shape of the handwritten signature has been taken into account as feature vector. Experimental results show that using both directional PDFs and the completely connected feedforward neural network classifier are valuable to build the first stage of a complete AHSVS.<>",
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"content": "The first stage of a complete automatic handwritten signature verification system (AHSVS) is described in this paper. Since only random forgeries are taken into account in this first stage of decision, the directional probability density function (PDF) which is related to the overall shape of the handwritten signature has been taken into account as feature vector. Experimental results show that using both directional PDFs and the completely connected feedforward neural network classifier are valuable to build the first stage of a complete AHSVS.<>",
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"Feature Extraction",
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"Probability",
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"affiliation": "Lab. de Modelisation Tridimensionnelle et d'Imagerie Ecole de Technol. Superieure, Montreal, Que., Canada",
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"title": "Offline Bengali Writer Verification by PDF-CNN and Siamese Net",
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"abstract": "Automated handwriting analysis is a popular area of research owing to the variation of writing patterns. In this research area, writer verification is one of the most challenging branches, having direct impact on biometrics and forensics. In this paper, we deal with offline writer verification on complex handwriting patterns. Therefore, we choose a relatively complex script, i.e., Indic Abugida script Bengali (or, Bangla) containing more than 250 compound characters. From a handwritten sample, the probability distribution functions (PDFs) of some handcrafted features are obtained and input to a convolutional neural network (CNN). For such a CNN architecture, we coin the term \"PDFCNN\", where handcrafted feature PDFs are hybridized with auto-derived CNN features. Such hybrid features are then fed into a Siamese neural network for writer verification. The experiments are performed on a Bengali offline handwritten dataset of 100 writers. Our system achieves encouraging results, which sometimes exceed the results of state-of-the-art techniques on writer verification.",
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"abstract": "Analytical expressions for the theoretical probability density function (pdf) of the LMS (least mean square) adaptive filter weights are obtained for the steady state. The LMS update is formulated as a stochastic differential equation and the weight PDF is derived as the solution to the Fokker-Planck equation. The application of systems identification is examined, and closed-form solutions are obtained for the steady-state PDF for the LMS weights. Only the steady-state PDFs are found for a system identification problem, although the theory developed can also be applied to finding the time-varying PDFs during the adaptation phase.<>",
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"abstract": "In this paper we propose a rigorous framework for texture image segmentation relying on region-based active contours (RBAC) and sparse texture representation. Such representations allow to efficiently describe a texture by transforming it in a dictionary of appropriate waveforms (atoms) where the texture representation coefficients are concentrated on a small set. For segmentation purposes. these atoms have to be multiscale and localized both in space and frequency, e.g. the wavelet transform. To discriminate different textures, we measure a ldquodistancerdquo between the non-parametric Parzen estimates of their respective sparse-representation coefficients probability density functions (pdfs). These distance measures are then used within RBAC, and we take benefit from shape derivative tools to derive the evolution speed expression of the RBAC. Our framework is applied to both supervised (with reference textures), and unsupervised texture segmentation. A series of experiments on synthetic textures illustrate the potential applicability of our method.",
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"content": "In this paper we propose a rigorous framework for texture image segmentation relying on region-based active contours (RBAC) and sparse texture representation. Such representations allow to efficiently describe a texture by transforming it in a dictionary of appropriate waveforms (atoms) where the texture representation coefficients are concentrated on a small set. For segmentation purposes. these atoms have to be multiscale and localized both in space and frequency, e.g. the wavelet transform. To discriminate different textures, we measure a ldquodistancerdquo between the non-parametric Parzen estimates of their respective sparse-representation coefficients probability density functions (pdfs). These distance measures are then used within RBAC, and we take benefit from shape derivative tools to derive the evolution speed expression of the RBAC. Our framework is applied to both supervised (with reference textures), and unsupervised texture segmentation. A series of experiments on synthetic textures illustrate the potential applicability of our method.",
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"fno": "04036585",
"keywords": [
"Edge Detection",
"Feature Extraction",
"Image Colour Analysis",
"Image Denoising",
"Poisson Equation",
"Flash Image Edge",
"Noflash Image Edge",
"Shadow Removal",
"Noise Reduction",
"Ambient Light Image",
"Color Space",
"Feature Space",
"Illuminant Change 3 Vector Direction",
"Gray Axis",
"Poissons Equation Inversion",
"Lighting",
"Pixel",
"Cameras",
"Poisson Equations",
"Graphics",
"Noise Reduction",
"Information Filtering",
"Information Filters",
"Tunneling",
"Filling"
],
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"affiliation": "School of Computing Science, Simon Fraser University, Vancouver, Canada V5A 1S6. mark@cs.sfu.ca",
"fullName": "Mark S. Drew",
"givenName": "Mark S.",
"surname": "Drew",
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{
"affiliation": "School of Computing Science, Simon Fraser University, Vancouver, Canada V5A 1S6. clu@cs.sfu.ca",
"fullName": "Cheng Lu",
"givenName": "Cheng",
"surname": "Lu",
"__typename": "ArticleAuthorType"
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{
"affiliation": "School of Computing Sciences, University of East Anglia, Norwich, U.K. NR4 7TJ. graham@cmp.uea.ac.uk",
"fullName": "Graham D. Finlayson",
"givenName": "Graham D.",
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"year": "2005",
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"article": {
"id": "12OmNC1Y5j5",
"doi": "10.1109/CGI.2005.1500434",
"title": "Light propagation for mixed polygonal and volumetric data",
"normalizedTitle": "Light propagation for mixed polygonal and volumetric data",
"abstract": "Some applications require scenes mixing polygonal and volumetric objects and shadows make the scenes more realistic. This paper describes a shadow algorithm for mixed polygonal and volumetric data, including the generation of soft shadows for area light sources. Our volume shader leverages advanced graphics GPU for an accelerated and feasible solution. The shadow and soft shadow algorithm applies to all combinations of volumes and polygons, without any restriction on the geometric positioning and overlap of the volumes and polygons. For realistic rendering where we have a high albedo participating media, multiple scattering is significant. We extend our algorithm to handle both multiple forward scattering and back scattering with light attenuation. This constitutes a complete system for shadow generation and light propagation.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Some applications require scenes mixing polygonal and volumetric objects and shadows make the scenes more realistic. This paper describes a shadow algorithm for mixed polygonal and volumetric data, including the generation of soft shadows for area light sources. Our volume shader leverages advanced graphics GPU for an accelerated and feasible solution. The shadow and soft shadow algorithm applies to all combinations of volumes and polygons, without any restriction on the geometric positioning and overlap of the volumes and polygons. For realistic rendering where we have a high albedo participating media, multiple scattering is significant. We extend our algorithm to handle both multiple forward scattering and back scattering with light attenuation. This constitutes a complete system for shadow generation and light propagation.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Some applications require scenes mixing polygonal and volumetric objects and shadows make the scenes more realistic. This paper describes a shadow algorithm for mixed polygonal and volumetric data, including the generation of soft shadows for area light sources. Our volume shader leverages advanced graphics GPU for an accelerated and feasible solution. The shadow and soft shadow algorithm applies to all combinations of volumes and polygons, without any restriction on the geometric positioning and overlap of the volumes and polygons. For realistic rendering where we have a high albedo participating media, multiple scattering is significant. We extend our algorithm to handle both multiple forward scattering and back scattering with light attenuation. This constitutes a complete system for shadow generation and light propagation.",
"fno": "01500434",
"keywords": [],
"authors": [
{
"affiliation": "Ohio State Univ., Columbus, OH, USA",
"fullName": "C. Zhang",
"givenName": "C.",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Ohio State Univ., Columbus, OH, USA",
"fullName": "D. Xue",
"givenName": "D.",
"surname": "Xue",
"__typename": "ArticleAuthorType"
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{
"affiliation": "Ohio State Univ., Columbus, OH, USA",
"fullName": "R. Crawfis",
"givenName": "R.",
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}
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{
"proceeding": {
"id": "1H1gVMlkl32",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
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"article": {
"id": "1H1hvFSItCU",
"doi": "10.1109/CVPR52688.2022.00537",
"title": "NeRFusion: Fusing Radiance Fields for Large-Scale Scene Reconstruction",
"normalizedTitle": "NeRFusion: Fusing Radiance Fields for Large-Scale Scene Reconstruction",
"abstract": "While NeRF [28] has shown great success for neural reconstruction and rendering, its limited MLP capacity and long per-scene optimization times make it challenging to model large-scale indoor scenes. In contrast, classical 3D reconstruction methods can handle large-scale scenes but do not produce realistic renderings. We propose NeRFusion, a method that combines the advantages of NeRF and TSDF-based fusion techniques to achieve efficient large-scale reconstruction and photo-realistic rendering. We process the input image sequence to predict per-frame local radiance fields via direct network inference. These are then fused using a novel recurrent neural network that incrementally reconstructs a global, sparse scene representation in real-time at 22 fps. This global volume can be further fine-tuned to boost rendering quality. We demonstrate that NeR-Fusionachieves state-of-the-art quality on both large-scale indoor and small-scale object scenes, with substantially faster reconstruction than NeRF and other recent methods.<sup>1</sup><sup>1</sup>https://jetd1.github.io/NeRFusion-Web/",
"abstracts": [
{
"abstractType": "Regular",
"content": "While NeRF [28] has shown great success for neural reconstruction and rendering, its limited MLP capacity and long per-scene optimization times make it challenging to model large-scale indoor scenes. In contrast, classical 3D reconstruction methods can handle large-scale scenes but do not produce realistic renderings. We propose NeRFusion, a method that combines the advantages of NeRF and TSDF-based fusion techniques to achieve efficient large-scale reconstruction and photo-realistic rendering. We process the input image sequence to predict per-frame local radiance fields via direct network inference. These are then fused using a novel recurrent neural network that incrementally reconstructs a global, sparse scene representation in real-time at 22 fps. This global volume can be further fine-tuned to boost rendering quality. We demonstrate that NeR-Fusionachieves state-of-the-art quality on both large-scale indoor and small-scale object scenes, with substantially faster reconstruction than NeRF and other recent methods.<sup>1</sup><sup>1</sup>https://jetd1.github.io/NeRFusion-Web/",
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],
"normalizedAbstract": "While NeRF [28] has shown great success for neural reconstruction and rendering, its limited MLP capacity and long per-scene optimization times make it challenging to model large-scale indoor scenes. In contrast, classical 3D reconstruction methods can handle large-scale scenes but do not produce realistic renderings. We propose NeRFusion, a method that combines the advantages of NeRF and TSDF-based fusion techniques to achieve efficient large-scale reconstruction and photo-realistic rendering. We process the input image sequence to predict per-frame local radiance fields via direct network inference. These are then fused using a novel recurrent neural network that incrementally reconstructs a global, sparse scene representation in real-time at 22 fps. This global volume can be further fine-tuned to boost rendering quality. We demonstrate that NeR-Fusionachieves state-of-the-art quality on both large-scale indoor and small-scale object scenes, with substantially faster reconstruction than NeRF and other recent methods.11https://jetd1.github.io/NeRFusion-Web/",
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"Image Sequences",
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"Ne RF 28",
"Neural Reconstruction",
"MLP Capacity",
"Per Scene Optimization Times",
"Large Scale Indoor Scenes",
"Classical 3 D Reconstruction Methods",
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"Realistic Renderings",
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"Photo Realistic Rendering",
"Input Image Sequence",
"Per Frame Local Radiance Fields",
"Direct Network Inference",
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"Sparse Scene Representation",
"Rendering Quality",
"Small Scale Object Scenes",
"Substantially Faster Reconstruction",
"Computer Vision",
"Recurrent Neural Networks",
"Three Dimensional Displays",
"Rendering Computer Graphics",
"Real Time Systems",
"Image Sequences",
"Pattern Recognition"
],
"authors": [
{
"affiliation": "University of California, San Diego",
"fullName": "Xiaoshuai Zhang",
"givenName": "Xiaoshuai",
"surname": "Zhang",
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"fullName": "Sai Bi",
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"fullName": "Kalyan Sunkavalli",
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"affiliation": "University of California, San Diego",
"fullName": "Hao Su",
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"affiliation": "Adobe Research",
"fullName": "Zexiang Xu",
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"title": "2020 International Conference on Culture-oriented Science & Technology (ICCST)",
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"article": {
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"doi": "10.1109/ICCST50977.2020.00012",
"title": "Research on traditional Chinese cultural material identification and database construction technology based on Mask R-CNN",
"normalizedTitle": "Research on traditional Chinese cultural material identification and database construction technology based on Mask R-CNN",
"abstract": "By studying the feature extraction technology of text materials, labelme feature extraction technology of Chinese cultural image materials based on spatial information and Mask RCNN image recognition technology, the classification and recognition method of image materials based on feature selection and combination is established to realize efficient semantic retrieval of text and image materials. Then we construct the material library of Chinese cultural elements. In this way, the material presented in the library can realize its reconstruction and apply in the field of cultural design.",
"abstracts": [
{
"abstractType": "Regular",
"content": "By studying the feature extraction technology of text materials, labelme feature extraction technology of Chinese cultural image materials based on spatial information and Mask RCNN image recognition technology, the classification and recognition method of image materials based on feature selection and combination is established to realize efficient semantic retrieval of text and image materials. Then we construct the material library of Chinese cultural elements. In this way, the material presented in the library can realize its reconstruction and apply in the field of cultural design.",
"__typename": "ArticleAbstractType"
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],
"normalizedAbstract": "By studying the feature extraction technology of text materials, labelme feature extraction technology of Chinese cultural image materials based on spatial information and Mask RCNN image recognition technology, the classification and recognition method of image materials based on feature selection and combination is established to realize efficient semantic retrieval of text and image materials. Then we construct the material library of Chinese cultural elements. In this way, the material presented in the library can realize its reconstruction and apply in the field of cultural design.",
"fno": "813800a034",
"keywords": [
"Convolutional Neural Nets",
"Feature Extraction",
"Image Classification",
"Image Reconstruction",
"Image Retrieval",
"Natural Language Processing",
"Text Analysis",
"Visual Databases",
"Material Library",
"Chinese Cultural Elements",
"Cultural Design",
"Database Construction Technology",
"Mask R CNN",
"Text Materials",
"Labelme Feature Extraction Technology",
"Chinese Cultural Image Materials",
"Mask RCNN Image Recognition Technology",
"Classification",
"Recognition Method",
"Feature Selection",
"Cultural Differences",
"Data Mining",
"Image Segmentation",
"Windows",
"Semantics",
"Search Engines",
"Libraries",
"Cultural Material",
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"abstract": "In this paper, we propose algorithms for biomolecular docking sites selection problem by various machine learning approaches with selective features reduction. The proposed method can reduce the number of various amino acid features before constructing machine learning prediction models. Given frame boxes with features, the proposed method analyzes the important features by correlation coefficients to LE values. The algorithm ranks these possible candidate locations on the receptor before launching AutoDock. Given a small molecular, namely ligand, it is a time-consuming task to compute the molecular docking against a large, relatively stationary molecule, or receptor. Our methods divide the surface area of receptor to several subspaces and evaluate these subspaces before choosing the promising subspaces to speed up the molecular docking simulation. The method is implemented upon the widely employed automated molecular docking simulation software package, AutoDock. The paper examines three different machine learning prediction models including the support vector machines (LIBSVM), deep neural networks (H2O), and the logistic regression model (AOD). The proposed affinity estimation algorithm, incorporated with a ligand-specific SVM prediction model, achieves about 4 folds faster comparing with original Autodock searching the whole surface of the receptor with similar binding energy score (LE, lowest engery) measurement. Furthermore, the proposed method can be easily parallelized in the implementation. Hadoop MapReduce frameworks are used in our experiments to parallelize the underlying massive computation works corresponding to ligand-receptor pairs examined under the experiment.",
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"abstract": "In this paper two methods of color image watermarking are proposed. Both methods use SVD and DCT-Walsh hybrid transform. First method uses SVD on column hybrid transformed host and watermark images. Second method uses SVD on sorted column hybrid transform coefficients of host and watermark images. In both methods, low frequency transform coefficients are used in contrast to traditional way of using middle frequency coefficients. In first method, 30 singular values of watermark are needed per plane to embed it in host. In second method, this number is drastically reduced to 3 values. This is possible because high energy compaction property of SVD gets further enhanced due to sorting of transform coefficients prior to SVD. Performance of both the methods is compared for robustness against various compression, noise addition, resizing, cropping, and histogram equalization.",
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"content": "In this paper two methods of color image watermarking are proposed. Both methods use SVD and DCT-Walsh hybrid transform. First method uses SVD on column hybrid transformed host and watermark images. Second method uses SVD on sorted column hybrid transform coefficients of host and watermark images. In both methods, low frequency transform coefficients are used in contrast to traditional way of using middle frequency coefficients. In first method, 30 singular values of watermark are needed per plane to embed it in host. In second method, this number is drastically reduced to 3 values. This is possible because high energy compaction property of SVD gets further enhanced due to sorting of transform coefficients prior to SVD. Performance of both the methods is compared for robustness against various compression, noise addition, resizing, cropping, and histogram equalization.",
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"title": "2015 International Conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)",
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"title": "Customer Authentication of Digital Imaging Using Hybrid Watermarking",
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"abstract": "In this paper, we present a robust and imperceptible hybrid watermarking method in order to be applied to digital color images with the purpose of detecting illegal copies, using a customer robust authentication. In order to improve the robustness of the proposed method against several common signal processing and geometrical attacks, two different algorithms for embedding a unique watermark are used. The watermark is composed by a binary pattern obtained from a cryptographic hash of the customer data. Discrete Fourier Transform (DFT) and a bi-dimensional histogram, both into the YCbCr color model domain, are used to embed the watermark bit sequence. The quality of the watermarked image is measured using the following well-known indices peak signal to noise ratio (PSNR), mean square error (MSE) and structural similarity index (SSIM). Experimental results show the robustness of the proposed method preserving at the same time a high quality on the host image.",
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"content": "In this paper, we present a robust and imperceptible hybrid watermarking method in order to be applied to digital color images with the purpose of detecting illegal copies, using a customer robust authentication. In order to improve the robustness of the proposed method against several common signal processing and geometrical attacks, two different algorithms for embedding a unique watermark are used. The watermark is composed by a binary pattern obtained from a cryptographic hash of the customer data. Discrete Fourier Transform (DFT) and a bi-dimensional histogram, both into the YCbCr color model domain, are used to embed the watermark bit sequence. The quality of the watermarked image is measured using the following well-known indices peak signal to noise ratio (PSNR), mean square error (MSE) and structural similarity index (SSIM). Experimental results show the robustness of the proposed method preserving at the same time a high quality on the host image.",
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"affiliation": null,
"fullName": "Manuel Cedillo-Hernández",
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"fullName": "Antonio Cedillo-Hernández",
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"fullName": "Carlos Aldair Roman-Balbuena",
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"fullName": "Francisco Garcia-Ugalde",
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"fullName": "Mariko Nakano-Miyatake",
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"fullName": "Hector Manuel Perez-Meana",
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"abstract": "A robust and geometric invariant digital image watermarking scheme based on SIFT Based Feature Points Detector (SIFTFPD) and histogram distribution is proposed in this paper. The SIFTFPD is proposed to extract geometric invariant feature points from the host image for watermark embedding; and the descriptor is generated subsequently. With the feature extraction procedure, the circular regions centered at the extracted feature points and with the given radius are defined as embedding regions. For watermark embedding, some pixels are moved to form a specific pattern in the intensity-level histogram distribution in each embedding region, to indicate the watermark. For watermark extraction, the embedded regions are generated with the descriptor and according to the intensity-level histogram distribution in each region, the watermark can be extracted. Experimental results show that the proposed scheme is very robust against geometric distortion such as rotation, scaling, cropping, and affine transformation; and common signal processing, such as JPEG compression, median filtering, and Gaussian low-pass filtering.",
"abstracts": [
{
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"content": "A robust and geometric invariant digital image watermarking scheme based on SIFT Based Feature Points Detector (SIFTFPD) and histogram distribution is proposed in this paper. The SIFTFPD is proposed to extract geometric invariant feature points from the host image for watermark embedding; and the descriptor is generated subsequently. With the feature extraction procedure, the circular regions centered at the extracted feature points and with the given radius are defined as embedding regions. For watermark embedding, some pixels are moved to form a specific pattern in the intensity-level histogram distribution in each embedding region, to indicate the watermark. For watermark extraction, the embedded regions are generated with the descriptor and according to the intensity-level histogram distribution in each region, the watermark can be extracted. Experimental results show that the proposed scheme is very robust against geometric distortion such as rotation, scaling, cropping, and affine transformation; and common signal processing, such as JPEG compression, median filtering, and Gaussian low-pass filtering.",
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"normalizedAbstract": "A robust and geometric invariant digital image watermarking scheme based on SIFT Based Feature Points Detector (SIFTFPD) and histogram distribution is proposed in this paper. The SIFTFPD is proposed to extract geometric invariant feature points from the host image for watermark embedding; and the descriptor is generated subsequently. With the feature extraction procedure, the circular regions centered at the extracted feature points and with the given radius are defined as embedding regions. For watermark embedding, some pixels are moved to form a specific pattern in the intensity-level histogram distribution in each embedding region, to indicate the watermark. For watermark extraction, the embedded regions are generated with the descriptor and according to the intensity-level histogram distribution in each region, the watermark can be extracted. Experimental results show that the proposed scheme is very robust against geometric distortion such as rotation, scaling, cropping, and affine transformation; and common signal processing, such as JPEG compression, median filtering, and Gaussian low-pass filtering.",
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"proceeding": {
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"title": "2020 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)",
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"title": "Reversible Database Watermarking Based on Random Forest and Genetic Algorithm",
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"abstract": "The advancing information technology is playing more and more important role in data mining of relational database.<sup>1</sup> The transfer and sharing of databases cause the copyright-related security threats. Database watermarking technology can effectively solve the problem with copyright protection and traceability, which has been attracting researchers' attention. In this paper, we proposed a novel, robust and reversible database watermarking technique, named histogram shifting watermarking based on random forest and genetic algorithm (RF-GAHCSW). It greatly improves the watermark capacity by means of histogram width reduction and eliminates the impact of the prediction error attack. Meanwhile, random forest algorithm is used to select important attributes for watermark embedding, and genetic algorithm is employed to find the optimal secret key for the database grouping and determine the position of watermark embedding to improve the watermark capacity and reduce data distortion. The experimental results show that the robustness of RF-GAHCSW is greatly improved, compared with the original HSW, and the distortion has little effect on the usability of database.",
"abstracts": [
{
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"content": "The advancing information technology is playing more and more important role in data mining of relational database.<sup>1</sup> The transfer and sharing of databases cause the copyright-related security threats. Database watermarking technology can effectively solve the problem with copyright protection and traceability, which has been attracting researchers' attention. In this paper, we proposed a novel, robust and reversible database watermarking technique, named histogram shifting watermarking based on random forest and genetic algorithm (RF-GAHCSW). It greatly improves the watermark capacity by means of histogram width reduction and eliminates the impact of the prediction error attack. Meanwhile, random forest algorithm is used to select important attributes for watermark embedding, and genetic algorithm is employed to find the optimal secret key for the database grouping and determine the position of watermark embedding to improve the watermark capacity and reduce data distortion. The experimental results show that the robustness of RF-GAHCSW is greatly improved, compared with the original HSW, and the distortion has little effect on the usability of database.",
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"normalizedAbstract": "The advancing information technology is playing more and more important role in data mining of relational database.1 The transfer and sharing of databases cause the copyright-related security threats. Database watermarking technology can effectively solve the problem with copyright protection and traceability, which has been attracting researchers' attention. In this paper, we proposed a novel, robust and reversible database watermarking technique, named histogram shifting watermarking based on random forest and genetic algorithm (RF-GAHCSW). It greatly improves the watermark capacity by means of histogram width reduction and eliminates the impact of the prediction error attack. Meanwhile, random forest algorithm is used to select important attributes for watermark embedding, and genetic algorithm is employed to find the optimal secret key for the database grouping and determine the position of watermark embedding to improve the watermark capacity and reduce data distortion. The experimental results show that the robustness of RF-GAHCSW is greatly improved, compared with the original HSW, and the distortion has little effect on the usability of database.",
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"keywords": [
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"authors": [
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"affiliation": "College of Computer Nanjing University of Posts and Telecommunications,Nanjing,China",
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"affiliation": "College of Computer Nanjing University of Posts and Telecommunications,Nanjing,China",
"fullName": "Yuxin Sun",
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"affiliation": "College of Computer Nanjing University of Posts and Telecommunications,Nanjing,China",
"fullName": "Yunlong Di",
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"affiliation": "Jiang Su Frontier Electric Technology Co. Ltd.,Nanjing,China",
"fullName": "Yongjin Zhu",
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"affiliation": "Jiang Su Frontier Electric Technology Co. Ltd.,Nanjing,China",
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{
"affiliation": "College of Computer Nanjing University of Posts and Telecommunications,Nanjing,China",
"fullName": "Yingzhou Zhang",
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"surname": "Zhang",
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"abstract": "In order to complete the semi auto-segmentation of dual-source CT image of heart and extract the structure of heart accurately, propose a novel segmentation method of CT images based on graph cuts based active contour and anisotropies spreads algorithms. The method combines image characteristics with high-level segmentation model, Due to effectively used heart anatomical structure, the noise and fuzzy boundary have less effect on the segmentation results. It is used to quickly and accurately segment ventricle, atria and coronary artery. After the pre-segmentation of the DSCT images, the ventricular and atrium are fast and accurately segmented through minimize the energy function. The segmentation method can effectively process cardiac medical image of DSCT. It provides new methods for clinical doctors to get more information of cardiac images.",
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"abstract": "Automatic coronary artery centerline extraction from 3D CT Angiography (CTA) has significant clinical importance for diagnosis of atherosclerotic heart disease. The focus of past literature is dominated by segmenting the complete coronary artery system as trees by computer. Though the labeling of different vessel branches (defined by their medical semantics) is much needed clinically, this task has been performed manually. In this paper, we propose a hierarchical machine learning approach to tackle the problem of tubular structure parsing in medical imaging. It has a progressive three-tiered classification process at volumetric voxel level, vessel segment level, and inter-segment level. Generative models are employed to project from low-level, ambiguous data to class-conditional probabilities; and discriminative classifiers are trained on the upper-level structural patterns of probabilities to label and parse the vessel segments. Our method is validated by experiments of detecting and segmenting clinically defined coronary arteries, from the initial noisy vessel segment networks generated by low-level heuristics-based tracing algorithms. The proposed framework is also generically applicable to other tubular structure parsing tasks.",
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"content": "Computed tomography (CT) is one of the most imaging methods widely used to locate lesions such as nodules, tumors, and cysts, and make primary diagnosis. For clearer imaging of anatomical or lesions, contrast-enhanced CT (CECT) scans are imaging with injecting a contrast agent into a patient during examination. But there are limits to iodine contrast injections so that CECT scans are not convenient like non-contrast enhanced CT (NECT). Recently, deep learning models bring impressive results in computer vision, including image translation. So, we would like to apply image translation methods to generate CECT images from the more accessible NECT images, and evaluate the effects of generated images on image detection tasks. In this study, we propose a method called cross-modal enhancement training strategy for thyroid anatomy detection, which employs CycleGAN to translate non-constrast enhanced CT images to enhanced CT style images with content reserved. The experiments are conducted on thyroid CT images with anatomy object annotation. The experimental results show that by adding translated images into the training dataset, the performance of thyroid anatomy detection can be effectively improved. We achieve the best mAP of 82.5% compared to 73.2% in the along non-contrast enhanced CT training.",
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"affiliation": "Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876",
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"affiliation": "Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876",
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"abstract": "Recently, interest in MR-only treatment planning using synthetic CTs (synCTs) has grown rapidly in radiation therapy. However, developing class solutions for medical images that contain atypical anatomy remains a major limitation. In this paper, we propose a novel spatial attention-guided generative adversarial network (attention-GAN) model to generate accurate synCTs using Tl-weighted MRI images as the input to address atypical anatomy. Experimental results on fifteen brain cancer patients show that attention-GAN outperformed existing synCT models and achieved an average MAE of 85.22±12.08, 232.41±60.86, 246.38±42.67 Hounsfield units between synCT and CT-SIM across the entire head, bone and air regions, respectively. Qualitative analysis shows that attention-GAN has the ability to use spatially focused areas to better handle outliers, areas with complex anatomy or post-surgical regions, and thus offer strong potential for supporting near real-time MR-only treatment planning.",
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"content": "Recently, interest in MR-only treatment planning using synthetic CTs (synCTs) has grown rapidly in radiation therapy. However, developing class solutions for medical images that contain atypical anatomy remains a major limitation. In this paper, we propose a novel spatial attention-guided generative adversarial network (attention-GAN) model to generate accurate synCTs using Tl-weighted MRI images as the input to address atypical anatomy. Experimental results on fifteen brain cancer patients show that attention-GAN outperformed existing synCT models and achieved an average MAE of 85.22±12.08, 232.41±60.86, 246.38±42.67 Hounsfield units between synCT and CT-SIM across the entire head, bone and air regions, respectively. Qualitative analysis shows that attention-GAN has the ability to use spatially focused areas to better handle outliers, areas with complex anatomy or post-surgical regions, and thus offer strong potential for supporting near real-time MR-only treatment planning.",
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"abstract": "Accurate and fast haptic simulations of deformable objects are desired in many applications such as medical virtual reality. In the haptic interactions with a coarse model, the number of nodes near the haptic interaction region is too small to generate detailed deformation. Thus local refinement techniques need to be developed. Many approaches have employed purely geometric subdivision schemes but they are not proper in describing deformation behavior of deformable object. This paper presents a continuum mechanics-based finite element adaptive method to perform a haptic interaction with a deformable object. It is accomplished by superimposing a local fine mesh upon a global coarse model which consists of the entire deformable object. The coupling between the local mesh and the global mesh is achieved by s-version finite element method (s-FEM) which is generally used to enhance more accurate solutions near the target points. The employment of s-FEM demonstrates the reliable deformation to users in real-time manner.",
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"content": "Accurate and fast haptic simulations of deformable objects are desired in many applications such as medical virtual reality. In the haptic interactions with a coarse model, the number of nodes near the haptic interaction region is too small to generate detailed deformation. Thus local refinement techniques need to be developed. Many approaches have employed purely geometric subdivision schemes but they are not proper in describing deformation behavior of deformable object. This paper presents a continuum mechanics-based finite element adaptive method to perform a haptic interaction with a deformable object. It is accomplished by superimposing a local fine mesh upon a global coarse model which consists of the entire deformable object. The coupling between the local mesh and the global mesh is achieved by s-version finite element method (s-FEM) which is generally used to enhance more accurate solutions near the target points. The employment of s-FEM demonstrates the reliable deformation to users in real-time manner.",
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"abstract": "In this paper we describe scalable parallel algorithms for building the Convex Hull and a Triangulation of a given point set in R/sup 2/. These algorithms are designed for the coarse grained multicomputer model: p processors with O(n/p)/spl Gt/O(1) local memory each, connected to some arbitrary interconnection network (e.g. mesh, hypercube, omega). They require time O(T/sub sequential//p+T/sub s/(n, p)), where T/sub s/(n, p) refers to the time of a global sort of n data on a p processor machine. Furthermore, they involve only a constant number of global communication rounds. Since computing either 2d Convex Hull or Triangulation requires time T/sub sequential/=/spl Theta/(n log n n) these algorithms either ran in optimal time, /spl Theta/(/sup n log n///sub p/), or in sort time, T/sub s/(n, p), for the interconnection network in question. These results become optimal when T/sub sequential//p dominates T/sub s/(n, p), for instance when randomized sorting algorithms are used, or for interconnection networks like the mesh for which optimal sorting algorithms exist.",
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"content": "In this paper we describe scalable parallel algorithms for building the Convex Hull and a Triangulation of a given point set in R/sup 2/. These algorithms are designed for the coarse grained multicomputer model: p processors with O(n/p)/spl Gt/O(1) local memory each, connected to some arbitrary interconnection network (e.g. mesh, hypercube, omega). They require time O(T/sub sequential//p+T/sub s/(n, p)), where T/sub s/(n, p) refers to the time of a global sort of n data on a p processor machine. Furthermore, they involve only a constant number of global communication rounds. Since computing either 2d Convex Hull or Triangulation requires time T/sub sequential/=/spl Theta/(n log n n) these algorithms either ran in optimal time, /spl Theta/(/sup n log n///sub p/), or in sort time, T/sub s/(n, p), for the interconnection network in question. These results become optimal when T/sub sequential//p dominates T/sub s/(n, p), for instance when randomized sorting algorithms are used, or for interconnection networks like the mesh for which optimal sorting algorithms exist.",
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"content": "This paper presents an ef.cient algorithm for the reconstruction of a multivariate function from multiple sets of scattered data. Given N sets of scattered data representing N distinct dependent variables that have been sampled independently over a common domain and N error tolerance values the algorithm constructs a triangulation of the domain of the data and associates multivariate values with the vertices of the triangulation. The resulting linear interpolation of these multivariate values yields a multivariate function, called a co-triangulation, that represents all of the dependent data up to the given error tolerance. A simple iterative algorithm for the construction of a cotriangulation from any number of data sets is presented and analyzed. The main contribution of this paper lies in the description of a highly efficient framework for the realization of this approximation algorithm. While the asymptotic time complexity of the algorithm certainly remains within the theoretical bounds, we demonstrate that it is possible to achieve running times that depend only linearly on the number of data even for very large problems with above two million samples. This efficient realization of the algorithm uses adapted dynamic data-structures and careful caching in an integrated framework.",
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"affiliation": "Rice University",
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"affiliation": "Rice University",
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"abstract": "The authors present four new parallel algorithms for triangulation of points in a plane. The first two, for one-way iterative arrays and two-way cellular arrays, requiring O(n) time and O(n) processors. Next they give an algorithm for d-dimensional mesh arrays which requires O(n/sup 1/d/) time and a hypercube algorithm with a worst case running time of O(log/sup 3/ n) and an expected running time of O(log/sup 2/ n), both using O(n) processors. The linear array algorithms are the first known of for these architectures which compute Delaunay and greedy triangulations. The mesh array and hypercube algorithms appear to be the first which directly compute a triangulation on these architectures. These algorithms can be modified to compute the Voronoi diagram of points in the plane and the convex hull of points in 3-space.",
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{
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"content": "The authors present four new parallel algorithms for triangulation of points in a plane. The first two, for one-way iterative arrays and two-way cellular arrays, requiring O(n) time and O(n) processors. Next they give an algorithm for d-dimensional mesh arrays which requires O(n/sup 1/d/) time and a hypercube algorithm with a worst case running time of O(log/sup 3/ n) and an expected running time of O(log/sup 2/ n), both using O(n) processors. The linear array algorithms are the first known of for these architectures which compute Delaunay and greedy triangulations. The mesh array and hypercube algorithms appear to be the first which directly compute a triangulation on these architectures. These algorithms can be modified to compute the Voronoi diagram of points in the plane and the convex hull of points in 3-space.",
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"fno": "00153750",
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"Delaunay Triangulations",
"Plane",
"3 D Convex Hull",
"Mesh Connected Arrays",
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"Two Way Cellular Arrays",
"Hypercube Algorithm",
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"Greedy Triangulations",
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"title": "2017 19th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)",
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"id": "17D45Xq6dCt",
"doi": "10.1109/SYNASC.2017.00028",
"title": "Effective Construction of Convex Hull Algorithms",
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"abstract": "Finding the convex hull of a set of points in a plane is one of the most common problems in computational geometry. We survey known algorithms for solving this problem and look into methods of their effective and parallel implementation. A simple generator of random input datasets is created, with an option to control the number of points on the resulting hull. We implement all surveyed algorithms along with their optimizations and compare them using our generator. Our measurements show, that Quickhull algorithm using optimizations proposed by Hoang and Linh [1] has the best performance among the implemented methods and is faster than the current state of the art libraries.",
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"abstract": "Hydrodynamics (inviscid fluid and irrotational flow) of rigid bodies with three mutually perpendicular plans of symmetry (orthotropic shapes) moving in confined media (wall, channel etc.) is analyzed by applying Lamé's functions and ellipsoidal harmonics. Towards this goal, a general numerical scheme for computing ellipsoidal harmonics of arbitrary order and degree is presented. In order to demonstrate the versatility of the method, which maybe is useful in many practical applications in mathematical physics, we chose to analytically address here the case of a tri-axial rigid ellipsoidal vessel moving steadily near a rigid wall or along the center of a two-dimensional channel. Free-surface effects are ignored and we are mainly interested in determining the dependence of the hydrodynamic added-mass coefficient and the asymmetric pressure (suction) force exerted on the body due to external flow disturbances such as nearby planar boundaries or flow producing mechanisms (singularities) simulating for example a propulsive system.",
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"abstract": "We propose DoubleFusion, a new real-time system that combines volumetric dynamic reconstruction with data-driven template fitting to simultaneously reconstruct detailed geometry, non-rigid motion and the inner human body shape from a single depth camera. One of the key contributions of this method is a double layer representation consisting of a complete parametric body shape inside, and a gradually fused outer surface layer. A pre-defined node graph on the body surface parameterizes the non-rigid deformations near the body, and a free-form dynamically changing graph parameterizes the outer surface layer far from the body, which allows more general reconstruction. We further propose a joint motion tracking method based on the double layer representation to enable robust and fast motion tracking performance. Moreover, the inner body shape is optimized online and forced to fit inside the outer surface layer. Overall, our method enables increasingly denoised, detailed and complete surface reconstructions, fast motion tracking performance and plausible inner body shape reconstruction in real-time. In particular, experiments show improved fast motion tracking and loop closure performance on more challenging scenarios.",
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"abstract": "Objective quality assessment plays a crucial role in the evaluation and optimization processes of Virtual Reality (VR) technologies, for which state-of-the-art objective quality evaluation metrics for omnidirectional video, i.e., 360 degree video, are typically derived from traditional MSE (or PSNR). Here we propose an objective omnidirectional video quality assessment method based on structural similarity (SSIM) in the spherical domain. Adopting the relationship of the structural similarity between the 2-D plane and sphere, the interference brought by the projection between the two domains can be well handled in the assessment process. The performance of the proposed spherical structural similarity (S-SSIM) index is evaluated with a subjective omnidirectional video quality assessment database. As demonstrated in the experimental results, the proposed S-SSIM outperforms state-of-the-art objective quality assessment metrics in omnidirectional video quality assessment.",
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{
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"content": "Objective quality assessment plays a crucial role in the evaluation and optimization processes of Virtual Reality (VR) technologies, for which state-of-the-art objective quality evaluation metrics for omnidirectional video, i.e., 360 degree video, are typically derived from traditional MSE (or PSNR). Here we propose an objective omnidirectional video quality assessment method based on structural similarity (SSIM) in the spherical domain. Adopting the relationship of the structural similarity between the 2-D plane and sphere, the interference brought by the projection between the two domains can be well handled in the assessment process. The performance of the proposed spherical structural similarity (S-SSIM) index is evaluated with a subjective omnidirectional video quality assessment database. As demonstrated in the experimental results, the proposed S-SSIM outperforms state-of-the-art objective quality assessment metrics in omnidirectional video quality assessment.",
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"fno": "08486584",
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"Indexes",
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"Distortion Measurement",
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"360 Degree Video"
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{
"affiliation": "School of Computer Science, Wuhan University, Wuhan, China",
"fullName": "Sijia Chen",
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{
"affiliation": "School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China",
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{
"affiliation": "School of Computer Science, Wuhan University, Wuhan, China",
"fullName": "Yiming Li",
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{
"affiliation": "School of Computer Science, Wuhan University, Wuhan, China",
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{
"affiliation": "Department of Electrical and Computer Engineering, University of Waterloo, Canada",
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