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"abstract": "Light field analysis recently received growing interest, since its rich structure information benefits many computer vision tasks. This paper presents a novel method to reconstruct continuous depth maps from light field data. Conventional approaches usually treat depth map reconstruction as an optimization problem with discrete labels. On the contrary, our proposed method can obtain continuous depth maps by solving a linear system, which preserves richer details compared with conventional discrete approaches. Structure tensor is employed to extract raw depth information and corresponding confidence levels from the light field data. We introduce a method to reduce the adverse effect of unreliable local estimations, which helps to get rid of errors in specular areas and edges where depth values are discontinuous. Experiments on both synthetic and real light field data demonstrate the effectiveness of the proposed method.",
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"abstract": "We present a novel multi-view stereo method designed for image-based rendering that generates piecewise planar depth maps from an unordered collection of photographs.",
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"abstract": "Data with multiple uncertain labels are common in many situations. For examples, a movie may be associated with multiple genres with different levels of confidence, and a protein sequence may be probabilistically assigned to several structural subcategories. Despite their ubiquity, the problem of visualizing uncertain labels has not been adequately addressed. Existing approaches often either discard the uncertainty information, or map the data to a low-dimensional subspace where their associations with multiple labels are obscured. In this paper, we propose a novel visual mining technique, UnTangle, for visualizing uncertain multi-labels. In our proposed visualization, data items are placed inside a web of connected triangles, with labels assigned to the triangle vertices such that nearby labels are more relevant to each other. The positions of the data items are determined based on the probabilistic associations between items and labels. UnTangle provides both (a) an automatic label placement algorithm, and (b) adaptive interaction mechanisms that allow users to control the label positioning for different visual queries. Our work makes a unique contribution by providing an effective way to investigate the relationship between data items and their uncertain labels, as well as the relationships among labels. Our user study suggests that the visualization effectively helps users discover emergent patterns and compare the nuances of uncertainty information in the data labels.",
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"abstract": "Despite the availability of a huge amount of video data accompanied by descriptive texts, it is not always easy to exploit the information contained in natural language in order to automatically recognize video concepts. Towards this goal, in this paper we use textual cues as means of supervision, introducing two weakly supervised techniques that extend the Multiple Instance Learning (MIL) framework: the Fuzzy Sets Multiple Instance Learning (FSMIL) and the Probabilistic Labels Multiple Instance Learning (PLMIL). The former encodes the spatio-temporal imprecision of the linguistic descriptions with Fuzzy Sets, while the latter models different interpretations of each description's semantics with Probabilistic Labels, both formulated through a convex optimization algorithm. In addition, we provide a novel technique to extract weak labels in the presence of complex semantics, that consists of semantic similarity computations. We evaluate our methods on two distinct problems, namely face and action recognition, in the challenging and realistic setting of movies accompanied by their screenplays, contained in the COGNIMUSE database. We show that, on both tasks, our method considerably outperforms a state-of-the-art weakly supervised approach, as well as other baselines.",
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"abstract": "In order to evaluate the fracture toughness of concrete, this article has employed extended finite element method (XFEM) to predict the maximal fracture loading of three-point bending beam with initial notch. The result of numerical test has manifested the limited loading is about 57 KN, which would induce the directed fracture over cross concrete beam. When the loading magnitude is about 0.5 times of the limited loading, a shakedown situation would happen, and the concrete would not occur unsteadily and ultimate fracture under this loading conditions.",
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"doi": "10.1109/ICDMA.2012.128",
"title": "Modeling and Validation of Windscreen Laminated Glass Behavior during Fracture",
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"abstract": "The objective of the study is to provide a method to simulate the mechanical behavior of windscreen laminated glass. The polyvinyl butyral (PVB) laminated glass is manufactured by pressing a layer of PVB film in between two pieces of glass plates under the high temperature condition. In this study, windscreen models are developed using different combination of glass and PVB with various connection types and two mesh sizes (5mm & 10mm). Then each windscreen model was impacted with standard adult headform under LS-DYNA environment and the results were compared with the experimental data reported in the literature. The results show that the behavior of windscreen developed with double layered shell elements of glass and PVB each with tied element connection simulates best the test results. Furthermore, the influence of fracture stress of glass on the above mentioned windscreen was investigated. It was observed that the area of crack and the peak value of headform acceleration are determined by the critical fracture stress and 50MPa fracture stress of glass best predicts the headform acceleration level and the cracks of windscreen.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The objective of the study is to provide a method to simulate the mechanical behavior of windscreen laminated glass. The polyvinyl butyral (PVB) laminated glass is manufactured by pressing a layer of PVB film in between two pieces of glass plates under the high temperature condition. In this study, windscreen models are developed using different combination of glass and PVB with various connection types and two mesh sizes (5mm & 10mm). Then each windscreen model was impacted with standard adult headform under LS-DYNA environment and the results were compared with the experimental data reported in the literature. The results show that the behavior of windscreen developed with double layered shell elements of glass and PVB each with tied element connection simulates best the test results. Furthermore, the influence of fracture stress of glass on the above mentioned windscreen was investigated. It was observed that the area of crack and the peak value of headform acceleration are determined by the critical fracture stress and 50MPa fracture stress of glass best predicts the headform acceleration level and the cracks of windscreen.",
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"normalizedAbstract": "The objective of the study is to provide a method to simulate the mechanical behavior of windscreen laminated glass. The polyvinyl butyral (PVB) laminated glass is manufactured by pressing a layer of PVB film in between two pieces of glass plates under the high temperature condition. In this study, windscreen models are developed using different combination of glass and PVB with various connection types and two mesh sizes (5mm & 10mm). Then each windscreen model was impacted with standard adult headform under LS-DYNA environment and the results were compared with the experimental data reported in the literature. The results show that the behavior of windscreen developed with double layered shell elements of glass and PVB each with tied element connection simulates best the test results. Furthermore, the influence of fracture stress of glass on the above mentioned windscreen was investigated. It was observed that the area of crack and the peak value of headform acceleration are determined by the critical fracture stress and 50MPa fracture stress of glass best predicts the headform acceleration level and the cracks of windscreen.",
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"title": "A Mass Spring Model for Physically-Realistic Haptic Rendering of Deformable Objects",
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"abstract": "Mass-spring systems (MSS) are extensively used for haptic rendering of soft materials due to ease of implementation for real-time simulations. One of the major challenges in using MSS is determination of system parameters such as node mass, spring stiffness, spring damping coefficients and mesh topology. Most of the proposed approaches to determine model parameters are either application specific or limited to a specific choice of material properties. In earlier work, we have presented a square MSS topology that incorporates additional springs to ensure physically realistic simulations, and provided a method to compute mass and spring parameters analytically based upon properties of the material. In this work, we demonstrate the effectiveness of the proposed MSS structure in simulating dynamic interactions through haptic simulations of a tapping task using a Phantom haptic device. Further, we show that the MSS structure can be used for haptic simulations involving large deformations through a membrane indentation experiment.",
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"affiliation": "Don Bosco Institute of Technology,Department of Mechanical Engineering,Mumbai,India",
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"content": "Directionally reinforced composites are widely used in numerous applications due to their appealing cost-to-strength ratio and further research about their fracture mechanisms is required to improve their durability. Few international standards have been developed for the mechanical characterization of directionally-reinforced fibre composites by considering three-point and four-point bending test evaluations. The aim of this study is to probe into the suitability of numerical simulations in terms of three-point and four-point bending to investigate the fracture mechanisms in directionally-reinforced fibre composites. In order to achieve this aim, two material models, namely a homogeneous and inhomogeneous consisting of a directionally reinforced structure were numerically simulated in three-point and four-point bending test setups. The results showed that 4-point bending simulation was better suited to investigate fracture in structures with a large span-to-depth as good correlation was established with previous experimental studies from literature. Directionally-reinforced fibre composites tend to exhibit fracture by delamination over a larger span section of the beam. Findings of this study showed that four-point bending test would yield more accurate results when evaluating directionally-reinforced fibre composite materials as a greater portion of the beam would be subjected to a constant bending moment. Moreover, stress concentration and compression zone due to extensive loading at puncher-specimen contact location, were found to be minimized through this test setup. Key findings of this study about 4-point bending test will be useful to further investigate the complex fracture phenomenon observed in composite materials.",
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"affiliation": "University of Mauritius,Faculty of Engineering,Mechanical & Production Engineering Department,Reduit,Mauritius",
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"title": "A soft hand model for physically-based manipulation of virtual objects",
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"abstract": "We developed a new hand model for increasing the robustness of finger-based manipulations of virtual objects. Each phalanx of our hand model consists of a number of deformable soft bodies, which dynamically adapt to the shape of grasped objects based on the applied forces. Stronger forces directly result in larger contact areas, which increase the friction between hand and object as would occur in reality. For a robust collision-based soft body simulation, we extended the lattice-shape matching algorithm to work with adaptive stiffness values, which are dynamically derived from force and velocity thresholds. Our implementation demonstrates that this approach allows very precise and robust grasping, manipulation and releasing of virtual objects and performs in real-time for a variety of complex scenarios. Additionally, laborious tuning of object and friction parameters is not necessary for the wide range of objects that we typically grasp with our hands.",
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"abstract": "A number of cameras have been introduced that sweep the focal plane using mechanical motion. However, mechanical motion makes video capture impractical and is unsuitable for long focal length cameras. In this paper, we present a focal sweep telephoto camera that uses a variable focus lens to sweep the focal plane. Our camera requires no mechanical motion and is capable of sweeping the focal plane periodically at high speeds. We use our prototype camera to capture EDOF videos at 20fps, and demonstrate space-time refocusing for scenes with a wide depth range. In addition, we capture periodic focal stacks, and show how they can be used for several interesting applications such as video refocusing and trajectory estimation of moving objects.",
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"abstract": "With the heated trend of augmented reality (AR) and popularity of smart head-mounted devices, the development of natural human device interaction is important, especially the hand gesture based interaction. This paper presents a solution for the point gesture based interaction in the egocentric vision and its application. Firstly, a dataset named EgoFinger is established focusing on the pointing gesture for the egocentric vision. We discuss the dataset collection detail and as well the comprehensive analysis of this dataset, including background and foreground color distribution, hand occurrence likelihood, scale and pointing angle distribution of hand and finger, and the manual labeling error analysis. The analysis shows that the dataset covers substantial data samples in various environments and dynamic hand shapes. Furthermore, we propose a two-stage Faster R-CNN based hand detection and dual-target fingertip detection framework. Comparing with state-of-art tracking and detection algorithm, it performs the best in both hand and fingertip detection. With the large-scale dataset, we achieve fingertip detection error at about 12.22 pixels in 640px × 480px video frame. Finally, using the fingertip detection result, we design and implement an input system for the egocentric vision, i.e., Ego-Air-Writing. By considering the fingertip as a pen, the user with wearable glass can write character in the air and interact with system using simple hand gestures.",
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"abstract": "In egocentric videos, the face of a wearer capturing the video is never captured. This gives a false sense of security that the wearer’s privacy is preserved while sharing such videos. However, egocentric cameras are typically harnessed to wearer’s head, and hence, also capture wearer’s gait. Recent works have shown that wearer gait signatures can be extracted from egocentric videos, which can be used to determine if two egocentric videos have the same wearer. In a more damaging scenario, one can even recognize a wearer using hand gestures from egocentric videos, or identify a wearer in third person videos such as from a surveillance camera. We believe, this could be a death knell in sharing of egocentric videos, and fatal for egocentric vision research. In this work, we suggest a novel technique to anonymize egocentric videos, which create carefully crafted, but small, and imperceptible optical flow perturbations in an egocentric video’s frames. Importantly, these perturbations do not affect object detection or action/activity recognition from egocentric videos but are strong enough to dis-balance the gait recovery process. In our experiments on benchmark EPIC-Kitchens dataset, the proposed perturbation degrades the wearer recognition performance of [42], from 66.3% to 13.4%, while preserving the activity recognition performance of [10] from 89.6% to 87.4%. To test our anonymization with more wearer recognition techniques, we also developed a stronger, and more generalizable wearer recognition method based on camera egomotion cues. The approach achieves state-ofthe-art (SOTA) performance of 59.67% on EPIC-Kitchens, compared to 55.06% by [42]. However, the accuracy of our recognition technique also drops to 12% using the proposed anonymizing perturbations.",
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"content": "In egocentric videos, the face of a wearer capturing the video is never captured. This gives a false sense of security that the wearer’s privacy is preserved while sharing such videos. However, egocentric cameras are typically harnessed to wearer’s head, and hence, also capture wearer’s gait. Recent works have shown that wearer gait signatures can be extracted from egocentric videos, which can be used to determine if two egocentric videos have the same wearer. In a more damaging scenario, one can even recognize a wearer using hand gestures from egocentric videos, or identify a wearer in third person videos such as from a surveillance camera. We believe, this could be a death knell in sharing of egocentric videos, and fatal for egocentric vision research. In this work, we suggest a novel technique to anonymize egocentric videos, which create carefully crafted, but small, and imperceptible optical flow perturbations in an egocentric video’s frames. Importantly, these perturbations do not affect object detection or action/activity recognition from egocentric videos but are strong enough to dis-balance the gait recovery process. In our experiments on benchmark EPIC-Kitchens dataset, the proposed perturbation degrades the wearer recognition performance of [42], from 66.3% to 13.4%, while preserving the activity recognition performance of [10] from 89.6% to 87.4%. To test our anonymization with more wearer recognition techniques, we also developed a stronger, and more generalizable wearer recognition method based on camera egomotion cues. The approach achieves state-ofthe-art (SOTA) performance of 59.67% on EPIC-Kitchens, compared to 55.06% by [42]. However, the accuracy of our recognition technique also drops to 12% using the proposed anonymizing perturbations.",
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"normalizedAbstract": "In egocentric videos, the face of a wearer capturing the video is never captured. This gives a false sense of security that the wearer’s privacy is preserved while sharing such videos. However, egocentric cameras are typically harnessed to wearer’s head, and hence, also capture wearer’s gait. Recent works have shown that wearer gait signatures can be extracted from egocentric videos, which can be used to determine if two egocentric videos have the same wearer. In a more damaging scenario, one can even recognize a wearer using hand gestures from egocentric videos, or identify a wearer in third person videos such as from a surveillance camera. We believe, this could be a death knell in sharing of egocentric videos, and fatal for egocentric vision research. In this work, we suggest a novel technique to anonymize egocentric videos, which create carefully crafted, but small, and imperceptible optical flow perturbations in an egocentric video’s frames. Importantly, these perturbations do not affect object detection or action/activity recognition from egocentric videos but are strong enough to dis-balance the gait recovery process. In our experiments on benchmark EPIC-Kitchens dataset, the proposed perturbation degrades the wearer recognition performance of [42], from 66.3% to 13.4%, while preserving the activity recognition performance of [10] from 89.6% to 87.4%. To test our anonymization with more wearer recognition techniques, we also developed a stronger, and more generalizable wearer recognition method based on camera egomotion cues. The approach achieves state-ofthe-art (SOTA) performance of 59.67% on EPIC-Kitchens, compared to 55.06% by [42]. However, the accuracy of our recognition technique also drops to 12% using the proposed anonymizing perturbations.",
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"abstract": "We present a method for robust and accurate hand pose recognition from egocentric depth cameras. Our method combines CNN based hand pose estimation and joint locations based hand gesture recognition. In pose estimation stage, we use a hand geometry prior network to estimate the hand pose. In gesture recognition stage, we defined a hand language which based on a set of pre-define basic propositions, obtained by applying four predicate types to the fingers and palm states. The hand language is used to convert the estimated joint location to hand gesture. Our experimental results indicate that the method enables robust and accurate gesture recognition in self-occlusion environment.",
"abstracts": [
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"content": "We present a method for robust and accurate hand pose recognition from egocentric depth cameras. Our method combines CNN based hand pose estimation and joint locations based hand gesture recognition. In pose estimation stage, we use a hand geometry prior network to estimate the hand pose. In gesture recognition stage, we defined a hand language which based on a set of pre-define basic propositions, obtained by applying four predicate types to the fingers and palm states. The hand language is used to convert the estimated joint location to hand gesture. Our experimental results indicate that the method enables robust and accurate gesture recognition in self-occlusion environment.",
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"affiliation": null,
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"abstract": "Automatic Dependence Surveillance-Broadcast (ADS-B) is transforming all aspects of aviation, including commercial aircraft and unmanned aerial systems (UAS). ADS-B service broadcasts traffic information and flight information to improve aviation safety and efficiency in the air and on runways, reduce costs, and lessen harmful effects on the environment. However, due to its broadcast nature, on one hand, ADS-B is vulnerable to malicious cybersecurity attacks relevant to broadcasting; on the other hand, broadcasting could be leveraged to further improve the safety of aviation. The objective of this paper is to investigate how to enhance aviation security and safety by leveraging the inherent broadcast property of ADS-B. To be specific, we propose two novel schemes for enhancing aviation cybersecurity and safety, respectively. The first scheme, motivated by the fact that fountain codes have been successfully applied in various broadcasting scenarios for ensuring the reliability, we propose to leverage Fountain Code to enhance the security of ADS-B. The second scheme, which is based on information integration, to detect collaboratively the comprehensive weather information to enhance the safety of aviation. The performance evaluation results demonstrate the feasibility of integrating fountain codes with ADS-B for encryption and the feasibility of collaborative detection to bypass turbulent weather conditions. To our knowledge, our work is the first attempt to apply fountain code to enhance aviation security and safety.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Automatic Dependence Surveillance-Broadcast (ADS-B) is transforming all aspects of aviation, including commercial aircraft and unmanned aerial systems (UAS). ADS-B service broadcasts traffic information and flight information to improve aviation safety and efficiency in the air and on runways, reduce costs, and lessen harmful effects on the environment. However, due to its broadcast nature, on one hand, ADS-B is vulnerable to malicious cybersecurity attacks relevant to broadcasting; on the other hand, broadcasting could be leveraged to further improve the safety of aviation. The objective of this paper is to investigate how to enhance aviation security and safety by leveraging the inherent broadcast property of ADS-B. To be specific, we propose two novel schemes for enhancing aviation cybersecurity and safety, respectively. The first scheme, motivated by the fact that fountain codes have been successfully applied in various broadcasting scenarios for ensuring the reliability, we propose to leverage Fountain Code to enhance the security of ADS-B. The second scheme, which is based on information integration, to detect collaboratively the comprehensive weather information to enhance the safety of aviation. The performance evaluation results demonstrate the feasibility of integrating fountain codes with ADS-B for encryption and the feasibility of collaborative detection to bypass turbulent weather conditions. To our knowledge, our work is the first attempt to apply fountain code to enhance aviation security and safety.",
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"abstract": "We describe two psychophysical experiments where we have quantified how much humans can unknowingly be redirected by auditory stimuli. The experiments use a two-alternative-forced-choice task. We tested 19 subjects in two different experiments: (E1) discrimination between virtual and physical rotation, and (E2) discrimination of path curvature. In experiment E1 subjects performed rotations with different gains, and then had to choose whether the auditory perceived rotation was smaller or greater than the physical rotation. In experiment E2 subjects estimate the path curvature when walking a curved path in the real world while the visual display shows a straight path in the virtual world. Our results show that users can be turned physically about 20% percent more or 12% less than the perceived virtual rotation, and users can be redirected on a circular arc while they believe they are walking straight.",
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"content": "We describe two psychophysical experiments where we have quantified how much humans can unknowingly be redirected by auditory stimuli. The experiments use a two-alternative-forced-choice task. We tested 19 subjects in two different experiments: (E1) discrimination between virtual and physical rotation, and (E2) discrimination of path curvature. In experiment E1 subjects performed rotations with different gains, and then had to choose whether the auditory perceived rotation was smaller or greater than the physical rotation. In experiment E2 subjects estimate the path curvature when walking a curved path in the real world while the visual display shows a straight path in the virtual world. Our results show that users can be turned physically about 20% percent more or 12% less than the perceived virtual rotation, and users can be redirected on a circular arc while they believe they are walking straight.",
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"abstract": "Traditional hand geometry based personal verification systems offer limited performance and therefore suitable only for small scale applications. This paper investigates a new approach to achieve performance improvement for hand geometry systems by simultaneously acquiring three dimensional features from the presented hands. The proposed system utilizes a laser based 3D digitizer to acquire registered intensity and range images of the presented hands in a completely contact-free manner, without using any hand position restricting mechanism. Two new representations that characterize the local features on the finger surface are extracted from the acquired range images and are matched using the proposed matching metrics. The proposed approach is evaluated on a database of 177 users, with 10 hand images for each user acquired in two sessions. Our experimental results suggest that the proposed 3D hand geometry features have significant discriminatory information to reliably authenticate individuals. Our experimental results also demonstrate that the combination of 3D hand geometry features with 2D geometry features can be employed to significantly improve the performance from 2D hand geometry features alone.",
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"affiliation": "Department of Computing, The Hong Kong Polytechnic University, Kowloon, Hong Kong",
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"normalizedAbstract": "We address the texture level-of-detail problem for extremely large surfaces such as terrain during realtime, view-dependent rendering. A novel texture hierarchy is introduced based on 4-8 refinement of raster tiles, in which the texture grids in effect rotate 45 degrees for each level of refinement. This hierarchy provides twice as many levels of detail as conventional quadtree-style refinement schemes such as mipmaps, and thus provides per-pixel view-dependent filtering that is twice as close to the ideal cutoff frequency for an average pixel. Because of this more gradual change in low-pass filtering, and due to the more precise emulation of the ideal cutoff frequency, we find in practice that the transitions between texture levels of detail are not perceptible. This allows rendering systems to avoid the complexity and performance costs of per-pixel blending between texture levels of detail. The 4-8 texturing scheme is integrated into a variant of the Real-time Optimally Adapting Meshes (ROAM) algorithm for viewdependent multiresolution mesh generation. Improvements to ROAM included here are: the diamond data structure as a stream-lined replacement for the triangle bintree elements, the use of low-pass- filtered geometry patches in place of individual triangles, integration of 4-8 textures, and a simple out-of-core data access mechanism for texture and geometry tiles.",
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"affiliation": "University of California at Davis",
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"fullName": "Mark A. Duchaineau",
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"affiliation": "University of California at Davis",
"fullName": "Kenneth I. Joy",
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"abstract": "We present a general framework that couples the PaRSEC runtime system and the HiCMA numerical library to solve challenging 3D data-sparse problems. Though formally dense, many matrix operators possess a rank structured property that can be exploited during the most time-consuming computational phase, i.e., the matrix factorization. In particular, this work highlights how a software bundle powered by a task-based programming model can address the heterogeneous workloads engendered by compressing the dense operator. Using Tile Low-Rank (TLR) approximation, our approach consists in capturing the most significant information in each tile of the matrix using a threshold which satisfies the application's accuracy requirements. Matrix operations are performed on the compressed data layout, reducing memory footprint and algorithmic complexity. Our proposed software solution accommodates a range of traditional data structures of linear algebra, i.e., from dense and data-sparse to sparse, within a single matrix operation. Separation of concerns is at the heart: hardware-agnostic implementation, asynchronous execution with a dynamic runtime system, and high performance numerical kernels, to prepare scientific applications to embrace exascale opportunities. This ambition necessitates extensions to PaRSEC that incorporate information related to data structure and rank distribution into the runtime decision-making. We introduce two runtime optimizations to address the challenges encountered when confronted with a large rank disparity: (1) a trimming procedure performed at runtime to cut away data dependencies from the directed acyclic graph discovered to be no longer required after compression and (2) a rank-aware diamond-shaped data distribution to mitigate the load imbalance overheads, reduce data movement, and conserve memory foot-print. We assess our implementation using 3D unstructured mesh deformation based on Radial Basis Function (RBF) interpolation. We report performance results on two different high-performance supercomputers and compare against existing state-of-the-art implementation. Our implementation shows up to 7-fold on Shaheen II and 9-fold on Fugaku performance superiority in situations where the 3D unstructured mesh deformation application renders a matrix operator with low density. Our software framework solves a formally dense 3D problem with 52M mesh points on 65K cores in about half an hour. This multidisciplinary work emphasizes the need for runtime systems to go beyond their primary responsibility of task scheduling on massively parallel hardware system, by synergistically bridging matrix algebra libraries with scientific applications.",
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"abstract": "Image space occlusion culling is an useful approach to reduce the rendering load of large polygonal models. Like most large model techniques, it trades overhead costs with the rendering costs of the possibly occluded geometry. Meanwhile, modern graphics hardware supports occlusion culling, whereas they associate a significant query overhead, which hurts in particular, if the occlusion culling query itself was unsuccessful. In this paper, we propose the Occupancy Map - a compact, cache-optimized representation of coverage information - to reduce the number of costly but unsuccessful occlusion culling queries and to arrange multiple occlusion queries. The information of the Occupancy Map is used to skip an occlusion query, if the respective map area is not yet set - the respective area has not yet received rendered pixels -, hence an occlusion query would always return not occluded. The remaining occlusion information is efficiently determined by asynchronous multiple occlusion queries with hardware-supported query functionality. To avoid redundant results, we arrange these multiple occlusion queries according to the information of several Occupancy Maps. Our presented technique is conservative and benefits from a partial depth order of the geometry.",
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"content": "Image space occlusion culling is an useful approach to reduce the rendering load of large polygonal models. Like most large model techniques, it trades overhead costs with the rendering costs of the possibly occluded geometry. Meanwhile, modern graphics hardware supports occlusion culling, whereas they associate a significant query overhead, which hurts in particular, if the occlusion culling query itself was unsuccessful. In this paper, we propose the Occupancy Map - a compact, cache-optimized representation of coverage information - to reduce the number of costly but unsuccessful occlusion culling queries and to arrange multiple occlusion queries. The information of the Occupancy Map is used to skip an occlusion query, if the respective map area is not yet set - the respective area has not yet received rendered pixels -, hence an occlusion query would always return not occluded. The remaining occlusion information is efficiently determined by asynchronous multiple occlusion queries with hardware-supported query functionality. To avoid redundant results, we arrange these multiple occlusion queries according to the information of several Occupancy Maps. Our presented technique is conservative and benefits from a partial depth order of the geometry.",
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"abstract": "One of the reasons that topological methods have a limited popularity for the visualization of complex 3D flow fields is the fact that such topological structures contain a number of separating stream surfaces. Since these stream surfaces tend to hide each other as well as other topological features, for complex 3D topologies the visualizations become cluttered and hardly interpretable. This paper proposes to use particular stream lines called saddle connectors instead of separating stream surfaces and to depict single surfaces only on user demand. We discuss properties and computational issues of saddle connectors and apply these methods to complex flow data. We show that the use of saddle connectors makes topological skeletons available as a valuable visualization tool even for topologically complex 3D flow data.",
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"content": "One of the reasons that topological methods have a limited popularity for the visualization of complex 3D flow fields is the fact that such topological structures contain a number of separating stream surfaces. Since these stream surfaces tend to hide each other as well as other topological features, for complex 3D topologies the visualizations become cluttered and hardly interpretable. This paper proposes to use particular stream lines called saddle connectors instead of separating stream surfaces and to depict single surfaces only on user demand. We discuss properties and computational issues of saddle connectors and apply these methods to complex flow data. We show that the use of saddle connectors makes topological skeletons available as a valuable visualization tool even for topologically complex 3D flow data.",
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"doi": "10.1109/VIS.2005.48",
"title": "HOT- Lines: Tracking Lines in Higher Order Tensor Fields",
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"abstract": "Tensors occur in many areas of science and engineering. Especially, they are used to describe charge, mass and energy transport (i.e. electrical conductivity tensor, diffusion tensor, thermal conduction tensor resp.) If the locale transport pattern is complicated, usual second order tensor representation is not sufficient. So far, there are no appropriate visualization methods for this case. We point out similarities of symmetric higher order tensors and spherical harmonics. A spherical harmonic representation is used to improve tensor glyphs. This paper unites the definition of streamlines and tensor lines and generalizes tensor lines to those applications where second order tensors representations fail. The algorithm is tested on the tractography problem in diffusion tensor magnetic resonance imaging (DT-MRI) and improved for this special application.",
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"affiliation": "Vienna University of Technology",
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"abstract": "Diffusion tensor imaging is a magnetic resonance imaging method which has gained increasing importance in neuroscience and especially in neurosurgery. It acquires diffusion properties represented by a symmetric 2nd order tensor for each voxel in the gathered dataset. From the medical point of view, the data is of special interest due to different diffusion characteristics of varying brain tissue allowing conclusions about the underlying structures such as white matter tracts. An obvious way to visualize this data is to focus on the anisotropic areas using the major eigenvector for tractography and rendering lines for visualization of the simulation results. Our approach extends this technique to avoid line representation since lines lead to very complex illustrations and furthermore are mistakable. Instead, we generate surfaces wrapping bundles of lines. Thereby, a more intuitive representation of different tracts is achieved.",
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