The Experts below are selected from a list of 30801 Experts worldwide ranked by ideXlab platform
Sakti Pramanik - One of the best experts on this subject based on the ideXlab platform.
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an efficient Path computation model for hierarchically structured topographical road maps
IEEE Transactions on Knowledge and Data Engineering, 2002Co-Authors: Sungwon Jung, Sakti PramanikAbstract:In this paper, we have developed a HiTi (Hierarchical MulTi) graph model for structuring large topographical road maps to speed up the minimum cost route computation. The HiTi graph model provides a novel approach to abstracting and structuring a topographical road map in a hierarchical fashion. We propose a new Shortest Path Algorithm named SPAH, which utilizes HiTi graph model of a topographical road map for its computation. We give the proof for the optimality of SPAH. Our performance analysis of SPAH on grid graphs showed that it significantly reduces the search space over existing methods. We also present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works on grid graphs. Within the HiTi graph framework, we also propose a parallel Shortest Path Algorithm named ISPAH. Experimental results show that inter query Shortest Path problem provides more opportunity for scalable parallelism than the intra query Shortest Path problem.
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an efficient Path computation model for hierarchically structured topographical road maps
IEEE Transactions on Knowledge and Data Engineering, 2002Co-Authors: Sungwon Jung, Sakti PramanikAbstract:In this paper, we have developed a HiTi (Hierarchical MulTi) graph model for structuring large topographical road maps to speed up the minimum cost route computation. The HiTi graph model provides a novel approach to abstracting and structuring a topographical road map in a hierarchical fashion. We propose a new Shortest Path Algorithm named SPAH, which utilizes HiTi graph model of a topographical road map for its computation. We give the proof for the optimality of SPAH. Our performance analysis of SPAH on grid graphs showed that it significantly reduces the search space over existing methods. We also present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works on grid graphs. Within the HiTi graph framework, we also propose a parallel Shortest Path Algorithm named ISPAH. Experimental results show that inter query Shortest Path problem provides more opportunity for scalable parallelism than the intra query Shortest Path problem.
Sungwon Jung - One of the best experts on this subject based on the ideXlab platform.
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an efficient Path computation model for hierarchically structured topographical road maps
IEEE Transactions on Knowledge and Data Engineering, 2002Co-Authors: Sungwon Jung, Sakti PramanikAbstract:In this paper, we have developed a HiTi (Hierarchical MulTi) graph model for structuring large topographical road maps to speed up the minimum cost route computation. The HiTi graph model provides a novel approach to abstracting and structuring a topographical road map in a hierarchical fashion. We propose a new Shortest Path Algorithm named SPAH, which utilizes HiTi graph model of a topographical road map for its computation. We give the proof for the optimality of SPAH. Our performance analysis of SPAH on grid graphs showed that it significantly reduces the search space over existing methods. We also present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works on grid graphs. Within the HiTi graph framework, we also propose a parallel Shortest Path Algorithm named ISPAH. Experimental results show that inter query Shortest Path problem provides more opportunity for scalable parallelism than the intra query Shortest Path problem.
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an efficient Path computation model for hierarchically structured topographical road maps
IEEE Transactions on Knowledge and Data Engineering, 2002Co-Authors: Sungwon Jung, Sakti PramanikAbstract:In this paper, we have developed a HiTi (Hierarchical MulTi) graph model for structuring large topographical road maps to speed up the minimum cost route computation. The HiTi graph model provides a novel approach to abstracting and structuring a topographical road map in a hierarchical fashion. We propose a new Shortest Path Algorithm named SPAH, which utilizes HiTi graph model of a topographical road map for its computation. We give the proof for the optimality of SPAH. Our performance analysis of SPAH on grid graphs showed that it significantly reduces the search space over existing methods. We also present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works on grid graphs. Within the HiTi graph framework, we also propose a parallel Shortest Path Algorithm named ISPAH. Experimental results show that inter query Shortest Path problem provides more opportunity for scalable parallelism than the intra query Shortest Path problem.
J. Kittler - One of the best experts on this subject based on the ideXlab platform.
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A Novel Data Association Algorithm for Object Tracking in Clutter with Application to Tennis Video Analysis
2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06), 2006Co-Authors: Fei Yan, A. Kostin, W. Christmas, J. KittlerAbstract:It is well recognised that data association is critically important for object tracking. However, in the presence of successive misdetections, a large number of false candidates and an unknown number of abrupt model switchings that happen unpredictably, the data association problem can be very difficult. We tackle these difficulties by using a layered data association scheme. At the object level, trajectories are "grown" from sets of object candidates that have high probabilities of containing only true positives; by this means the otherwise combinatorial complexity is significantly reduced. Dijkstra’s Shortest Path Algorithm is then used to perform data association at the trajectory level. The Algorithm is applied to low-quality tennis video sequences to track a tennis ball. Experiments show that the Algorithm is robust to abrupt model switchings, and performs well in heavily cluttered environments.
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a novel data association Algorithm for object tracking in clutter with application to tennis video analysis
Computer Vision and Pattern Recognition, 2006Co-Authors: Fei Yan, A. Kostin, W. Christmas, J. KittlerAbstract:It is well recognised that data association is critically important for object tracking. However, in the presence of successive misdetections, a large number of false candidates and an unknown number of abrupt model switchings that happen unpredictably, the data association problem can be very difficult. We tackle these difficulties by using a layered data association scheme. At the object level, trajectories are "grown" from sets of object candidates that have high probabilities of containing only true positives; by this means the otherwise combinatorial complexity is significantly reduced. Dijkstras Shortest Path Algorithm is then used to perform data association at the trajectory level. The Algorithm is applied to low-quality tennis video sequences to track a tennis ball. Experiments show that the Algorithm is robust to abrupt model switchings, and performs well in heavily cluttered environments.
Faouzi Kamoun - One of the best experts on this subject based on the ideXlab platform.
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neural networks for Shortest Path computation and routing in computer networks
IEEE Transactions on Neural Networks, 1993Co-Authors: Mehmet M Ali, Faouzi KamounAbstract:The application of neural networks to the optimum routing problem in packet-switched computer networks, where the goal is to minimize the network-wide average time delay, is addressed. Under appropriate assumptions, the optimum routing Algorithm relies heavily on Shortest Path computations that have to be carried out in real time. For this purpose an efficient neural network Shortest Path Algorithm that is an improved version of previously suggested Hopfield models is proposed. The general principles involved in the design of the proposed neural network are discussed in detail. Its computational power is demonstrated through computer simulations. One of the main features of the proposed model is that it will enable the routing Algorithm to be implemented in real time and also to be adaptive to changes in link costs and network topology. >
Peter Sanders - One of the best experts on this subject based on the ideXlab platform.
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δ stepping a parallelizable Shortest Path Algorithm
European Symposium on Algorithms, 2003Co-Authors: Ulrich Meyer, Peter SandersAbstract:The single source Shortest Path problem for arbitrary directed graphs with n nodes, m edges and nonnegative edge weights can sequentially be solved using O(n.log n + m) operations. However, no work-efficient parallel Algorithm is known that runs in sublinear time for arbitrary graphs. In this paper we present a rather simple Algorithm for the single source Shortest Path problem. Our new Algorithm, which we call Delta-stepping, can be implemented very efficiently in sequential and parallel setting for a large class of graphs. For random edge weights and arbitrary graphs with maximum node degree d, sequential Δ-stepping needs O(n + m + d.L) total average-case time, where L denotes the maximum Shortest Path weight from the source node s to any node reachable from s. For example, this means linear time on directed graphs with constant maximum degree. Our best parallel version for a PRAM takes O(d.L.log n + log 2 n) time and O(n + m + d L.log n) work on average. For random graphs, even O(log 2 n) time and O(n + m) work on average can be achieved. We also discuss how the Algorithm can be adapted to work with nonrandom edge weights and how it can be implemented on distributed memory machines. Experiments indicate that already a simple implementation of the Algorithm achieves significant speedup on real machines.
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delta stepping a parallel single source Shortest Path Algorithm
European Symposium on Algorithms, 1998Co-Authors: Ulrich Meyer, Peter SandersAbstract:In spite of intensive research, little progress has been made towards fast and work-efficient parallel Algorithms for the single source Shortest Path problem. Our Δ-stepping Algorithm, a generalization of Dial's Algorithm and the Bellman-Ford Algorithm, improves this situation at least in the following "average-case" sense: For random directed graphs with edge probability d/n and uniformly distributed edge weights a PRAM version works in expected time O(log3 n/ log log n) using linear work. The Algorithm also allows for efficient adaptation to distributed memory machines. Implementations show that our approach works on real machines. As a side effect, we get a simple linear time sequential Algorithm for a large class of not necessarily random directed graphs with random edge weights.
