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"abstract": "A skeletonization algorithm based on the Euclidean distance function using the sequential maxima-tracking method is described which, when applied to a connected image, generates a connected skeleton composed of simple digital arcs. With a slight modification, the algorithm can preserve the more important features in the skeletal branches which touch the object boundary at corners. Therefore its application to shape recognition can be easily achieved.<>",
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"abstract": "Skeleton representation of an object is believed to be a powerful representation that captures both boundary and region information of the object. The skeleton of a shape is a representation composed of idealized thin lines that preserve the connectivity or topology of the original shape. Although the literature contains a large number of skeletonization algorithms, many open problems remain. A new skeletonization approach that relies on the electrostatic field theory (EFT) is proposed. Many problems associated with existing skeletonization algorithms are solved using the proposed approach. In particular, connectivity, thinness, and other desirable features of a skeleton are guaranteed. Furthermore, the electrostatic field-based approach captures notions of corner detection, multiple scale, thinning, and skeletonization all within one unified framework. Experimental results are very encouraging and are used to illustrate the potential of the proposed approach.<>",
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"abstract": "Left ventricle(LV) motion estimation plays an important role in the diagnosis and treatment of cardiovascular diseases. To improve the accuracy of LV motion estimation, we propose a method by combining point set matching with surface structure features. Firstly, the normal direction of a point is estimated by an approximate approach, and is used to describe the structure feature of the point. Then, the Gaussian mixture model (GMM) is employed to describe the structure features of the points extracted from a LV image. The LV motion estimation is reformulated as the problem of minimizing a statistical discrepancy measure between two Gaussian mixtures. A new cost function is defined based on the distance between two point sets and the discrepancy measure between Gaussian mixtures of structure features of two point sets. Lastly, we solve the new cost function using the combination of Stochastic Gradient Descent (SGD) algorithm and Quasi-Newton method. We evaluate the performance of our method on a cardiac dataset of 33 subjects. Experiments results show that our method is robust when large parameters are needed to be solved. Moreover, the registration accuracy is improved compared to existing point set matching methods.",
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"abstract": "In this paper we define two bi-adaptive mesh filtering algorithms for efficient features preserving restoration of noisy models acquired from 3D scanners. The new filters are based on 2D image processing adaptive algorithms extended to 3D mesh processing. We combine two adaptive algorithms to design more efficient bi-adaptive algorithms. The first filter is applied on the mesh triangles normal vector orientation and the second filter is applied on the vertices normal vector orientation. Both filters are applied on adaptively selected local neighborhood based on a threshold angle between normal vectors. Then the algorithm to update the vertices position is also adaptive according to a local variance evaluation compared to a noise variance threshold. We compare our two bi-adaptive algorithms results to other filtering algorithms according to reliable error metrics and show the new filters outperform previous features preserving and adaptive mesh denoising methods.",
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"content": "In this paper we define two bi-adaptive mesh filtering algorithms for efficient features preserving restoration of noisy models acquired from 3D scanners. The new filters are based on 2D image processing adaptive algorithms extended to 3D mesh processing. We combine two adaptive algorithms to design more efficient bi-adaptive algorithms. The first filter is applied on the mesh triangles normal vector orientation and the second filter is applied on the vertices normal vector orientation. Both filters are applied on adaptively selected local neighborhood based on a threshold angle between normal vectors. Then the algorithm to update the vertices position is also adaptive according to a local variance evaluation compared to a noise variance threshold. We compare our two bi-adaptive algorithms results to other filtering algorithms according to reliable error metrics and show the new filters outperform previous features preserving and adaptive mesh denoising methods.",
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"abstract": "This paper presents a framework for rigid point-set registration and merging using a robust continuous data representation. Our point-set representation is constructed by training a one-class support vector machine with a Gaussian radial basis function kernel and subsequently approximating the output function with a Gaussian mixture model. We leverage the representation's sparse parametrisation and robustness to noise, outliers and occlusions in an efficient registration algorithm that minimises the L2 distance between our support vector -- parametrised Gaussian mixtures. In contrast, existing techniques, such as Iterative Closest Point and Gaussian mixture approaches, manifest a narrower region of convergence and are less robust to occlusions and missing data, as demonstrated in the evaluation on a range of 2D and 3D datasets. Finally, we present a novel algorithm, GMMerge, that parsimoniously and equitably merges aligned mixture models, allowing the framework to be used for reconstruction and mapping.",
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"abstract": "Organizing shapes by convex parts is a fundamental procedure for many shape-related applications. However, convexity is sensitive to noise and shape variations. Recent publications in the field concentrated on decomposing shapes into near-convex parts. Although a variety of methods have been presented, there is still a need for a robust and versatile method, especially when a shape possesses long curved branches such as a lizard with a long curved tail. It is difficult to capture the tail as a whole part because its concavity is too high based on classic measures. To address this issue, we propose a ‘Visibility Range’, novel shape signature in this paper. Visibility range reaches low values for points in concave regions and high values in convex regions. Moreover, a novel concavity measure based on visibility range is presented. Compared to previous measures, the novel measure describes long curved branches better. With these, a simple but effective shape decomposition algorithm is designed. The decomposition is formulated as a problem of detecting points with extreme visibility range in a visibility matrix. Extensive experiments have been done on shapes with various kinds of near-convex parts, demonstrating that the proposed method is more robust and effective than the state-of-art methods based on other concave-convex features.",
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"normalizedAbstract": "Intelligence Transportation System (ITS) plays a more and more important role in the daily life, such as transportation route planning, vehicle scheduling, prediction and so on. The speed data of the roads are the major data. However, the road speed data always contain partial missing data, which affect the performance of Intelligent Transport System. These missing traffic data are usually complemented by the current speed values of neighbor roads or the historical speed values of the road, but the completion results are not satisfied. Since traffic data has spatial-temporal correlation, some researches employ low rank matrix completion method to recover the traffic missing data and achieve wonderful experimental results. In actually, analyzing the traffic data, we can even know the exact rank of the traffic data, which is ignored by traditional nuclear norm based traffic data completion methods. We can firstly replace the nuclear norm with partial sum minimization of singular values constraint in conventional low matrix completion methods for traffic data completion. Then, we further to find the strong spatio-temporal correlation exist in traffic data; as a result, we introduce order constraint into our proposed method. A proper solution for the proposed methods is given. The proposed method is tested on two real road speed database, which demonstrate our proposed method is superior than the traditional traffic data completion methods.",
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"abstract": "This paper describes an italic font recognition method using stroke pattern analysis on wavelet decomposed word images. The word images are extracted from scanned text documents containing word objects in various fonts and styles. Earlier font recognition methods mainly focus on slanted texture or pattern analysis on single character or large text blocks, which are sensitive to noise and subject to font and style variations such as size, serifness, boldness, etc. Our method takes advantage of 2-D wavelet decomposition on each word image and performs statistical analysis on stroke patterns obtained from wavelet decomposed sub-images. Experiments are carried out with 22,384 frequently used word images in both normal and italic styles of four different fonts. On average, a recognition accuracy of 95.76% for normal style and 96.49% for italic style is achieved. Experiments conducted on word images extracted from scanned documents with scattered italic words also show an encouraging result.",
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"abstract": "Depth-dependent defocus results in a limited depth-of-field in consumer-level cameras. Computational imaging provides alternative solutions to resolve all-in-focus images with the assistance of designed optics and algorithms. In this work, we extend the concept of focal sweep from refractive optics to diffractive optics, where we fuse multiple focal powers onto one single element. In contrast to state-of-the-art sweep models, ours can generate better-conditioned point spread function (PSF) distributions along the expected depth range with drastically shortened (40%) sweep distance. Further by encoding axially asymmetric PSFs subject to color channels, and then sharing sharp information across channels, we preserve details as well as color fidelity. We prototype two diffractive imaging systems that work in the monochromatic and RGB color domain. Experimental results indicate that the depth-of-field can be significantly extended with fewer artifacts remaining after the deconvolution.",
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"doi": "10.1109/CVPR52688.2022.01916",
"title": "Quantization-aware Deep Optics for Diffractive Snapshot Hyperspectral Imaging",
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"abstract": "Diffractive snapshot hyperspectral imaging based on the deep optics framework has been striving to capture the spectral images of dynamic scenes. However, existing deep optics frameworks all suffer from the mismatch between the optical hardware and the reconstruction algorithm due to the quantization operation in the diffractive optical element (DOE) fabrication, leading to the limited performance of hyperspectral imaging in practice. In this paper, we propose the quantization-aware deep optics for diffractive snapshot hyperspectral imaging. Our key observation is that common lithography techniques used in fabricating DOEs need to quantize the DOE height map to a few levels, and can freely set the height for each level. Therefore, we propose to integrate the quantization operation into the DOE height map optimization and design an adaptive mechanism to adjust the physical height of each quantization level. According to the optimization, we fabricate the quantized DOE directly and build a diffractive hyperspectral snapshot imaging system. Our method develops the deep optics framework to be more practical through the awareness of and adaptation to the quantization operation of the DOE physical structure, making the fabricated DOE and the reconstruction algorithm match each other systematically. Extensive synthetic simulation and real hardware experiments validate the superior performance of our method.",
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"content": "Diffractive snapshot hyperspectral imaging based on the deep optics framework has been striving to capture the spectral images of dynamic scenes. However, existing deep optics frameworks all suffer from the mismatch between the optical hardware and the reconstruction algorithm due to the quantization operation in the diffractive optical element (DOE) fabrication, leading to the limited performance of hyperspectral imaging in practice. In this paper, we propose the quantization-aware deep optics for diffractive snapshot hyperspectral imaging. Our key observation is that common lithography techniques used in fabricating DOEs need to quantize the DOE height map to a few levels, and can freely set the height for each level. Therefore, we propose to integrate the quantization operation into the DOE height map optimization and design an adaptive mechanism to adjust the physical height of each quantization level. According to the optimization, we fabricate the quantized DOE directly and build a diffractive hyperspectral snapshot imaging system. Our method develops the deep optics framework to be more practical through the awareness of and adaptation to the quantization operation of the DOE physical structure, making the fabricated DOE and the reconstruction algorithm match each other systematically. Extensive synthetic simulation and real hardware experiments validate the superior performance of our method.",
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"affiliation": "Beijing Institute of Technology",
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"affiliation": "Beijing Normal University",
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"abstract": "Nowadays, high-power and multi-spectral lasers are used in many scientific experiments and industrial processes. Those laser sources can rapidly cause permanent damage to human eyes. Research and development work with those laser sources requires typically wearing personal protective equipment (PPE), such as laser safety goggles as eye protectors. Currently, laser safety goggles are based on optical spectral filters, which block spectral bands where hazardous laser radiation is emitted. Such laser safety goggles can filter up to 99% of the visible spectrum, rendering researchers working in hazardous and complex laboratory environments visually impaired. Video see-through head-mounted displays (VST-HMD) could be used as eye protectors without reducing users’ visibility of the environment since they can be constructed such that all laser and ambient light is blocked from the human eye. To date, this application domain is still largely unexplored in the MR community. To our best knowledge, there has been no comprehensive work that investigates the human factors of such an eye protection method at an advanced optics laboratory. In this work, we present the results of an empirical study where we evaluate the usability, perceived safety, advantages, and limitations of using VST-HMDs as laser safety goggles. We use a stereoscopic VST-HMD developed through a human-centered design approach at one of the most advanced optics laboratories in the world. 18 participants including 14 laser experts evaluated the current prototype. Our user evaluation and field studies confirm that the complex and hazardous working conditions at high-energy laser laboratories could be significantly improved with MR technology.",
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"content": "Nowadays, high-power and multi-spectral lasers are used in many scientific experiments and industrial processes. Those laser sources can rapidly cause permanent damage to human eyes. Research and development work with those laser sources requires typically wearing personal protective equipment (PPE), such as laser safety goggles as eye protectors. Currently, laser safety goggles are based on optical spectral filters, which block spectral bands where hazardous laser radiation is emitted. Such laser safety goggles can filter up to 99% of the visible spectrum, rendering researchers working in hazardous and complex laboratory environments visually impaired. Video see-through head-mounted displays (VST-HMD) could be used as eye protectors without reducing users’ visibility of the environment since they can be constructed such that all laser and ambient light is blocked from the human eye. To date, this application domain is still largely unexplored in the MR community. To our best knowledge, there has been no comprehensive work that investigates the human factors of such an eye protection method at an advanced optics laboratory. In this work, we present the results of an empirical study where we evaluate the usability, perceived safety, advantages, and limitations of using VST-HMDs as laser safety goggles. We use a stereoscopic VST-HMD developed through a human-centered design approach at one of the most advanced optics laboratories in the world. 18 participants including 14 laser experts evaluated the current prototype. Our user evaluation and field studies confirm that the complex and hazardous working conditions at high-energy laser laboratories could be significantly improved with MR technology.",
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"abstract": "Master/Slave Speculative Parallelization (MSSP) is an execution paradigm for improving the execution rate of sequential programs by parallelizing them speculatively for execution on a multiprocessor. In MSSP, one processor -- the master -- executes an approximate version of the program to compute selected values that the full program's execution is expected to compute. The master's results are checked by slave processors that execute the original program. This validation is parallelized by cutting the program's execution into tasks. Each slave uses its predicted inputs (as computed by the master) to validate the input predictions of the next task, inductively validating the entire execution. The performance of MSSP is largely determined by the execution rate of the approximate program. Since approximate code has no correctness requirements (in essence it is a software value predictor), it can be optimized more effectively than traditionally generated code. It is free to sacrifice correctness in the uncommon case to maximize performance in the common case. A simulation-based evaluation of an initial MSSP implementation achieves speedups of up to 1.7 (harmonic mean 1.25) on the SPEC2000 integer benchmarks. Performance is currently limited by the effectiveness with which our current automated infrastructure approximates programs, which can likely be improved significantly.",
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"abstract": "In order to solve the problem of rescue and safe operation in power industry, we design the live working robot whose structure and control method are introduced. We design the system solution of the force feedback and master-slave teleoperation robot for live working. Its structure and performance are optimized by kinematics, dynamics and finite element analysis. Besides, we build the kinematics model of the robot. Aiming at the problems of master-slave synchronous operation and force control in working process, teleoperation control method and force feedback control method are designed. Through the force feedback simulation experiment on WEBOTS, we verify that the force feedback control meets the design requirements. The feasibility of the method is verified by semi-physical simulation platform. Finally, experiments are carried out on the force feedback master-slave teleoperation robot, which verifies that the synchronization of the master-slave teleoperation meets the design requirements.",
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"title": "Attention based Occlusion Removal for Hybrid Telepresence Systems",
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"abstract": "Traditionally, video conferencing is a widely adopted solution for remote communication, but a lack of immersiveness comes inherently due to the 2D nature of facial representation. The integration of Virtual Reality (VR) in a communication/telepresence system through Head Mounted Displays (HMDs) promises to provide users with a much better immersive experience. However, HMDs cause hindrance by blocking the facial appearance and expressions of the user. We propose a novel attention-enabled encoder-decoder architecture for HMD de-occlusion to overcome these issues. We also propose to train our person-specific model using short videos of the user, captured in varying appearances, and demonstrated generalization to unseen poses and appearances of the user. We report superior qualitative and quantitative results over state-of-the-art methods. We also present applications of this approach to hybrid video teleconferencing using existing animation and 3D face reconstruction pipelines. Dataset is available at this website.",
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"content": "Traditionally, video conferencing is a widely adopted solution for remote communication, but a lack of immersiveness comes inherently due to the 2D nature of facial representation. The integration of Virtual Reality (VR) in a communication/telepresence system through Head Mounted Displays (HMDs) promises to provide users with a much better immersive experience. However, HMDs cause hindrance by blocking the facial appearance and expressions of the user. We propose a novel attention-enabled encoder-decoder architecture for HMD de-occlusion to overcome these issues. We also propose to train our person-specific model using short videos of the user, captured in varying appearances, and demonstrated generalization to unseen poses and appearances of the user. We report superior qualitative and quantitative results over state-of-the-art methods. We also present applications of this approach to hybrid video teleconferencing using existing animation and 3D face reconstruction pipelines. Dataset is available at this website.",
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"keywords": [
"Computer Animation",
"Face Recognition",
"Helmet Mounted Displays",
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"Image Representation",
"Teleconferencing",
"Virtual Reality",
"Occlusion Removal",
"Hybrid Telepresence Systems",
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"Widely Adopted Solution",
"Remote Communication",
"Facial Representation",
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"Head Mounted Displays",
"Immersive Experience",
"HM Ds Cause Hindrance",
"Facial Appearance",
"Expressions",
"Attention Enabled Encoder Decoder Architecture",
"HMD De Occlusion",
"Person Specific Model",
"Short Videos",
"Varying Appearances",
"Unseen Poses",
"Superior Qualitative Results",
"Hybrid Video Teleconferencing",
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"Solid Modeling",
"Three Dimensional Displays",
"Telepresence",
"Pipelines",
"Resists",
"Task Analysis",
"Face Image Inpainting",
"Facial De Occlusion",
"HMD Removal",
"Virtual Reality"
],
"authors": [
{
"affiliation": "IIIT Hyderabad,India",
"fullName": "Surabhi Gupta",
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"fullName": "Ashwath Shetty",
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{
"affiliation": "IIIT Hyderabad,India",
"fullName": "Avinash Sharma",
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"surname": "Sharma",
"__typename": "ArticleAuthorType"
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"pages": "167-174",
"year": "2022",
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"isbn": "978-1-6654-9774-9",
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