The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
S.d. Kollias - One of the best experts on this subject based on the ideXlab platform.
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ICIP (2) - Tube-embodied gradient vector flow fields for unsupervised Video Object Plane (VOP) segmentation
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001Co-Authors: K.s. Ntalianis, N.d. Doulamis, A.d. Doulamis, S.d. KolliasAbstract:In this paper constrained gradient vector flow (GVF) field generation is performed, for fast and accurate unsupervised stereoscopic semantic segmentation. The scheme utilizes the information provided by a depth segments map, produced by stereo analysis methods and incorporation of a segmentation algorithm. Then a Canny edge detector is applied to the depth region and produces an edge map. The edge map is used for tube estimation inside which the GVF field evolves. After generation of the GVF field an active contour is unsupervisedly initialized onto the outer bound of the tube. Finally a greedy approach is adopted and the active contour, guided by the GVF field, extracts the VOP. Experimental results on real life stereoscopic Video sequences indicate the efficiency of the proposed scheme.
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ICME - Multiresolution gradient vector flow field: a fast implementation towards Video Object Plane segmentation
IEEE International Conference on Multimedia and Expo 2001. ICME 2001., 2001Co-Authors: K.s. Ntalianis, N.d. Doulamis, A.d. Doulamis, S.d. KolliasAbstract:In this paper, an efficient scheme for Video Object segmentation is proposed. The scheme is based on a multiresolution Gradient Vector Flow field (M-GVF) and a Motion Geometric Space (MGS) formulation. In particular the proposed scheme is initialized from an Object approximation which can be provided either (a) automatically (unsupervised case) based on a depth map estimation method or (b) semi-automatically by user interaction. In the following, several feature points are estimated on the initial Object contour (i.e. depth Object) and an M-GVF adapted MGS is created to determine the direction that a feature point is allowed to move to. In this framework, each feature point moves onto its MGS in order to locate the contour of the physical Video Object. Experimental results are presented to indicate the reliable performance of the proposed scheme on real life stereoscopic and monocular Video sequences.
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multiresolution gradient vector flow field a fast implementation towards Video Object Plane segmentation
International Conference on Multimedia and Expo, 2001Co-Authors: K.s. Ntalianis, N.d. Doulamis, A.d. Doulamis, S.d. KolliasAbstract:In this paper, an efficient scheme for Video Object segmentation is proposed. The scheme is based on a multiresolution Gradient Vector Flow field (M-GVF) and a Motion Geometric Space (MGS) formulation. In particular the proposed scheme is initialized from an Object approximation which can be provided either (a) automatically (unsupervised case) based on a depth map estimation method or (b) semi-automatically by user interaction. In the following, several feature points are estimated on the initial Object contour (i.e. depth Object) and an M-GVF adapted MGS is created to determine the direction that a feature point is allowed to move to. In this framework, each feature point moves onto its MGS in order to locate the contour of the physical Video Object. Experimental results are presented to indicate the reliable performance of the proposed scheme on real life stereoscopic and monocular Video sequences.
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Tube-embodied gradient vector flow fields for unsupervised Video Object Plane (VOP) segmentation
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001Co-Authors: K.s. Ntalianis, N.d. Doulamis, A.d. Doulamis, S.d. KolliasAbstract:In this paper constrained gradient vector flow (GVF) field generation is performed, for fast and accurate unsupervised stereoscopic semantic segmentation. The scheme utilizes the information provided by a depth segments map, produced by stereo analysis methods and incorporation of a segmentation algorithm. Then a Canny edge detector is applied to the depth region and produces an edge map. The edge map is used for tube estimation inside which the GVF field evolves. After generation of the GVF field an active contour is unsupervisedly initialized onto the outer bound of the tube. Finally a greedy approach is adopted and the active contour, guided by the GVF field, extracts the VOP. Experimental results on real life stereoscopic Video sequences indicate the efficiency of the proposed scheme.
Haewook Choi - One of the best experts on this subject based on the ideXlab platform.
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ISPA - The optimum network on chip architectures for Video Object Plane decoder design
Parallel and Distributed Processing and Applications, 2006Co-Authors: Huynam Nguyen, Haewook ChoiAbstract:On Chip Network (OCN) has been proposed as a new methodology for addressing the design challenges of future massly integrated system in nanoscale. In this paper, three differently heterogenous Tree-based network topologies are proposed as the OCN architectures for Video Object Plane Decoder (VOPD). The topologies are designed in order to maximize the system throughput. This paper also evaluates the proposed topologies by comparing them to other conventional topologies such as 2-D Mesh and Fat-Tree with respects to throughput, power consumption and size. We use the power modelling tool, known as Orion model to calculate the static powers, areas, and dynamic energies of three topologies. The experiment results show that our Tree-based topologies offer similar throughputs as Fat-Tree does and much higher throughputs compared to 2-D Mesh while use less chip areas and power consumptions.
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the optimum network on chip architectures for Video Object Plane decoder design
Lecture Notes in Computer Science, 2006Co-Authors: Huynam Nguyen, Haewook ChoiAbstract:On Chip Network (OCN) has been proposed as a new methodology for addressing the design challenges of future massly integrated system in nanoscale. In this paper, three differently heterogenous Tree-based network topologies are proposed as the OCN architectures for Video Object Plane Decoder (VOPD). The topologies are designed in order to maximize the system throughput. This paper also evaluates the proposed topologies by comparing them to other conventional topologies such as 2-D Mesh and Fat-Tree with respects to throughput, power consumption and size. We use the power modelling tool, known as Orion model to calculate the static powers, areas, and dynamic energies of three topologies. The experiment results show that our Tree-based topologies offer similar throughputs as Fat-Tree does and much higher throughputs compared to 2-D Mesh while use less chip areas and power consumptions.
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Assessing Routing Behavior on On-Chip-Network
2006 International Conference on Computer Engineering and Systems, 2006Co-Authors: Huynam Nguyen, Haewook ChoiAbstract:Network-on-chip (NoC) is being proposed as a scalable and reusable communication platform for future SoC applications. An important problem in NoC design is deciding the type of routing which is one of the most crucial key factors that greatly affects the NoC architecture based systems performance. Currently, most of the proposals for routing in NoC are based upon deterministic routing mechanism because it gives better latency at low packet injection and requires less resources while guaranteeing an orderly packet arrival. However, the disadvantage of deterministic routing is that it cannot respond to dynamic network condition such as congestion. When the network becomes congested, adaptive routing provides better throughput and lower latency by allowing alternate paths. In this paper, using simulation, we evaluate the performance of adaptive routing algorithm to deterministic routing strategy respected to throughput, power consumption and latency. The simulation environment is 2D-mesh based NoC topology including different kinds of mapping Video Object Plane decoder (VOPD) application onto this architecture. The experiment results prove the adaptive routing performance under network congestion occurrence
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ICESS - Realization of Video Object Plane decoder on on-chip network architecture
Embedded Software and Systems, 2005Co-Authors: Huynam Nguyen, Haewook ChoiAbstract:System-on-chip (SoC) designs provide integrated solutions to challenging design problems in the telecommunications, multimedia, and so on. Present and future SoC are designed using pre-existing components which we call cores. Communication between the cores will become a major bottleneck for system performance as standard hardwired bus-based communication architectures will be inefficient in terms of throughput, latency and power consumption. To solve this problem, a packet switched platform that considers the delay and reliability issues of wires so called Network-on-Chip (NoC) has been proposed. In this paper, we present interconnected network topologies and analyze their performances with a particular application under bandwidth constrains. Then we compare the performances among different ways of mapping the cores onto a Mesh NoC architecture. The comparison between Mesh and Fat-Tree topology is also presented. These evaluations are done by utilizing NS-2, a tool that has been widely used in the computer network design.
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realization of Video Object Plane decoder on on chip network architecture
Lecture Notes in Computer Science, 2005Co-Authors: Huynam Nguyen, Haewook ChoiAbstract:System-on-chip (SoC) designs provide integrated solutions to challenging design problems in the telecommunications, multimedia, and so on. Present and future SoC are designed using pre-existing components which we call cores. Communication between the cores will become a major bottleneck for system performance as standard hardwired bus-based communication architectures will be inefficient in terms of throughput, latency and power consumption. To solve this problem, a packet switched platform that considers the delay and reliability issues of wires so called Network-on-Chip (NoC) has been proposed. In this paper, we present interconnected network topologies and analyze their performances with a particular application under bandwidth constrains. Then we compare the performances among different ways of mapping the cores onto a Mesh NoC architecture. The comparison between Mesh and Fat-Tree topology is also presented. These evaluations are done by utilizing NS-2, a tool that has been widely used in the computer network design.
K.n. Ngan - One of the best experts on this subject based on the ideXlab platform.
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Segmentation and tracking of moving Objects for content-based Video coding
IEE Proceedings - Vision Image and Signal Processing, 1999Co-Authors: T. Meier, K.n. NganAbstract:To enable content-based functionalities in Video coding, a decomposition of the scene into physical Objects is required. Such Objects are normally not characterised by homogeneous colour, intensity, or optical flow. Therefore, conventional techniques based on these low-level features cannot perform the desired segmentation. The authors address segmentation and tracking of moving Objects and present a new Video Object Plane (VOP) segmentation algorithm that extracts semantically meaningful Objects. A morphological motion filter detects physical Objects by identifying areas that are moving differently from the background. A new filter criterion is introduced that measures the deviation of the estimated local motion from the synthesised global motion. A two-dimensional binary model is derived for the Object of interest and tracked throughout the sequence by a Hausdorff Object tracker. To accommodate for rotations and changes in shape, the model is updated every frame by a two-stage method that accounts for rigid and non-rigid moving parts of the Object. The binary model then guides the actual VOP extraction, whereby a novel boundary post-processor ensures high boundary accuracy. Experimental results demonstrate the performance of the proposed algorithm.
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Video segmentation for content-based coding
IEEE Transactions on Circuits and Systems for Video Technology, 1999Co-Authors: T. Meier, K.n. NganAbstract:To provide multimedia applications with new functionalities, the new Video coding standard MPEG-4 relies on a content-based representation. This requires a prior decomposition of sequences into semantically meaningful, physical Objects. We formulate this problem as one of separating foreground Objects from the background based on motion information. For the Object of interest, a 2D binary model is derived and tracked throughout the sequence. The model points consist of edge pixels detected by the Canny operator. To accommodate rotation and changes in shape of the tracked Object, the model is updated every frame. These binary models then guide the actual Video Object Plane (VOP) extraction. Thanks to our new boundary postprocessor and the excellent edge localization properties of the Canny operator, the resulting VOP contours are very accurate. Both the model initialization and update stages exploit motion information. The main assumption underlying our approach is the existence of a dominant global motion that can be assigned to the background. Areas that do not follow this background motion indicate the presence of independently moving physical Objects. Two alternative methods to identify such Objects are presented. The first one employs a morphological motion filter with a new filter criterion, which measures the deviation of the locally estimated optical flow from the corresponding global motion. The second method computes a change detection mask by taking the difference between consecutive frames. The first version is more suitable for sequences with little motion, whereas the second version is better at dealing with faster moving or changing Objects. Experimental results demonstrate the performance of our algorithm.
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Video Object Plane segmentation using a morphological motion filter and Hausdorff Object tracking
Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269), 1998Co-Authors: T. Meier, K.n. NganAbstract:This paper considers the decomposition of Video sequences into so-called Video Object Planes, which is required for the content-based representation of visual Objects in MPEG-4. A new segmentation algorithm is described that identifies physical Objects using a morphological motion filter. For the Object of interest, a two-dimensional binary model is derived based on areas in the scene that are moving differently from the background. This model is updated each frame to pick up possible rotation and changes in shape of the Object. Temporal correspondence is established by a Hausdorff Object tracker: The binary model sequences guide the actual Video Object Plane extraction. Since the model points correspond to edges detected by the Canny operator; a high Object boundary location is achieved. Experimental results demonstrate that our proposed technique can successfully extract the physical Object from Video sequences.
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Automatic segmentation of moving Objects for Video Object Plane generation
IEEE Transactions on Circuits and Systems for Video Technology, 1998Co-Authors: T. Meier, K.n. NganAbstract:The new Video coding standard MPEG-4 is enabling content-based functionalities. It takes advantage of a prior decomposition of sequences into Video Object Planes (VOPs) so that each VOP represents one moving Object. A comprehensive review summarizes some of the most important motion segmentation and VOP generation techniques that have been proposed. Then, a new automatic Video sequence segmentation algorithm that extracts moving Objects is presented. The core of this algorithm is an Object tracker that matches a two-dimensional (2-D) binary model of the Object against subsequent frames using the Hausdorff distance. The best match found indicates the translation the Object has undergone, and the model is updated every frame to accommodate for rotation and changes in shape. The initial model is derived automatically, and a new model update method based on the concept of moving connected components allows for comparatively large changes in shape. The proposed algorithm is improved by a filtering technique that removes stationary background. Finally, the binary model sequence guides the extraction Objects of the VOPs from the sequence. Experimental results demonstrate the performance of our algorithm.
K.s. Ntalianis - One of the best experts on this subject based on the ideXlab platform.
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ICIP (2) - Tube-embodied gradient vector flow fields for unsupervised Video Object Plane (VOP) segmentation
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001Co-Authors: K.s. Ntalianis, N.d. Doulamis, A.d. Doulamis, S.d. KolliasAbstract:In this paper constrained gradient vector flow (GVF) field generation is performed, for fast and accurate unsupervised stereoscopic semantic segmentation. The scheme utilizes the information provided by a depth segments map, produced by stereo analysis methods and incorporation of a segmentation algorithm. Then a Canny edge detector is applied to the depth region and produces an edge map. The edge map is used for tube estimation inside which the GVF field evolves. After generation of the GVF field an active contour is unsupervisedly initialized onto the outer bound of the tube. Finally a greedy approach is adopted and the active contour, guided by the GVF field, extracts the VOP. Experimental results on real life stereoscopic Video sequences indicate the efficiency of the proposed scheme.
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ICME - Multiresolution gradient vector flow field: a fast implementation towards Video Object Plane segmentation
IEEE International Conference on Multimedia and Expo 2001. ICME 2001., 2001Co-Authors: K.s. Ntalianis, N.d. Doulamis, A.d. Doulamis, S.d. KolliasAbstract:In this paper, an efficient scheme for Video Object segmentation is proposed. The scheme is based on a multiresolution Gradient Vector Flow field (M-GVF) and a Motion Geometric Space (MGS) formulation. In particular the proposed scheme is initialized from an Object approximation which can be provided either (a) automatically (unsupervised case) based on a depth map estimation method or (b) semi-automatically by user interaction. In the following, several feature points are estimated on the initial Object contour (i.e. depth Object) and an M-GVF adapted MGS is created to determine the direction that a feature point is allowed to move to. In this framework, each feature point moves onto its MGS in order to locate the contour of the physical Video Object. Experimental results are presented to indicate the reliable performance of the proposed scheme on real life stereoscopic and monocular Video sequences.
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multiresolution gradient vector flow field a fast implementation towards Video Object Plane segmentation
International Conference on Multimedia and Expo, 2001Co-Authors: K.s. Ntalianis, N.d. Doulamis, A.d. Doulamis, S.d. KolliasAbstract:In this paper, an efficient scheme for Video Object segmentation is proposed. The scheme is based on a multiresolution Gradient Vector Flow field (M-GVF) and a Motion Geometric Space (MGS) formulation. In particular the proposed scheme is initialized from an Object approximation which can be provided either (a) automatically (unsupervised case) based on a depth map estimation method or (b) semi-automatically by user interaction. In the following, several feature points are estimated on the initial Object contour (i.e. depth Object) and an M-GVF adapted MGS is created to determine the direction that a feature point is allowed to move to. In this framework, each feature point moves onto its MGS in order to locate the contour of the physical Video Object. Experimental results are presented to indicate the reliable performance of the proposed scheme on real life stereoscopic and monocular Video sequences.
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Tube-embodied gradient vector flow fields for unsupervised Video Object Plane (VOP) segmentation
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001Co-Authors: K.s. Ntalianis, N.d. Doulamis, A.d. Doulamis, S.d. KolliasAbstract:In this paper constrained gradient vector flow (GVF) field generation is performed, for fast and accurate unsupervised stereoscopic semantic segmentation. The scheme utilizes the information provided by a depth segments map, produced by stereo analysis methods and incorporation of a segmentation algorithm. Then a Canny edge detector is applied to the depth region and produces an edge map. The edge map is used for tube estimation inside which the GVF field evolves. After generation of the GVF field an active contour is unsupervisedly initialized onto the outer bound of the tube. Finally a greedy approach is adopted and the active contour, guided by the GVF field, extracts the VOP. Experimental results on real life stereoscopic Video sequences indicate the efficiency of the proposed scheme.
Huynam Nguyen - One of the best experts on this subject based on the ideXlab platform.
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ISPA - The optimum network on chip architectures for Video Object Plane decoder design
Parallel and Distributed Processing and Applications, 2006Co-Authors: Huynam Nguyen, Haewook ChoiAbstract:On Chip Network (OCN) has been proposed as a new methodology for addressing the design challenges of future massly integrated system in nanoscale. In this paper, three differently heterogenous Tree-based network topologies are proposed as the OCN architectures for Video Object Plane Decoder (VOPD). The topologies are designed in order to maximize the system throughput. This paper also evaluates the proposed topologies by comparing them to other conventional topologies such as 2-D Mesh and Fat-Tree with respects to throughput, power consumption and size. We use the power modelling tool, known as Orion model to calculate the static powers, areas, and dynamic energies of three topologies. The experiment results show that our Tree-based topologies offer similar throughputs as Fat-Tree does and much higher throughputs compared to 2-D Mesh while use less chip areas and power consumptions.
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the optimum network on chip architectures for Video Object Plane decoder design
Lecture Notes in Computer Science, 2006Co-Authors: Huynam Nguyen, Haewook ChoiAbstract:On Chip Network (OCN) has been proposed as a new methodology for addressing the design challenges of future massly integrated system in nanoscale. In this paper, three differently heterogenous Tree-based network topologies are proposed as the OCN architectures for Video Object Plane Decoder (VOPD). The topologies are designed in order to maximize the system throughput. This paper also evaluates the proposed topologies by comparing them to other conventional topologies such as 2-D Mesh and Fat-Tree with respects to throughput, power consumption and size. We use the power modelling tool, known as Orion model to calculate the static powers, areas, and dynamic energies of three topologies. The experiment results show that our Tree-based topologies offer similar throughputs as Fat-Tree does and much higher throughputs compared to 2-D Mesh while use less chip areas and power consumptions.
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Assessing Routing Behavior on On-Chip-Network
2006 International Conference on Computer Engineering and Systems, 2006Co-Authors: Huynam Nguyen, Haewook ChoiAbstract:Network-on-chip (NoC) is being proposed as a scalable and reusable communication platform for future SoC applications. An important problem in NoC design is deciding the type of routing which is one of the most crucial key factors that greatly affects the NoC architecture based systems performance. Currently, most of the proposals for routing in NoC are based upon deterministic routing mechanism because it gives better latency at low packet injection and requires less resources while guaranteeing an orderly packet arrival. However, the disadvantage of deterministic routing is that it cannot respond to dynamic network condition such as congestion. When the network becomes congested, adaptive routing provides better throughput and lower latency by allowing alternate paths. In this paper, using simulation, we evaluate the performance of adaptive routing algorithm to deterministic routing strategy respected to throughput, power consumption and latency. The simulation environment is 2D-mesh based NoC topology including different kinds of mapping Video Object Plane decoder (VOPD) application onto this architecture. The experiment results prove the adaptive routing performance under network congestion occurrence
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ICESS - Realization of Video Object Plane decoder on on-chip network architecture
Embedded Software and Systems, 2005Co-Authors: Huynam Nguyen, Haewook ChoiAbstract:System-on-chip (SoC) designs provide integrated solutions to challenging design problems in the telecommunications, multimedia, and so on. Present and future SoC are designed using pre-existing components which we call cores. Communication between the cores will become a major bottleneck for system performance as standard hardwired bus-based communication architectures will be inefficient in terms of throughput, latency and power consumption. To solve this problem, a packet switched platform that considers the delay and reliability issues of wires so called Network-on-Chip (NoC) has been proposed. In this paper, we present interconnected network topologies and analyze their performances with a particular application under bandwidth constrains. Then we compare the performances among different ways of mapping the cores onto a Mesh NoC architecture. The comparison between Mesh and Fat-Tree topology is also presented. These evaluations are done by utilizing NS-2, a tool that has been widely used in the computer network design.
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realization of Video Object Plane decoder on on chip network architecture
Lecture Notes in Computer Science, 2005Co-Authors: Huynam Nguyen, Haewook ChoiAbstract:System-on-chip (SoC) designs provide integrated solutions to challenging design problems in the telecommunications, multimedia, and so on. Present and future SoC are designed using pre-existing components which we call cores. Communication between the cores will become a major bottleneck for system performance as standard hardwired bus-based communication architectures will be inefficient in terms of throughput, latency and power consumption. To solve this problem, a packet switched platform that considers the delay and reliability issues of wires so called Network-on-Chip (NoC) has been proposed. In this paper, we present interconnected network topologies and analyze their performances with a particular application under bandwidth constrains. Then we compare the performances among different ways of mapping the cores onto a Mesh NoC architecture. The comparison between Mesh and Fat-Tree topology is also presented. These evaluations are done by utilizing NS-2, a tool that has been widely used in the computer network design.
