The Experts below are selected from a list of 147 Experts worldwide ranked by ideXlab platform
Pham Dinh Thanh - One of the best experts on this subject based on the ideXlab platform.
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multifactorial evolutionary algorithm for inter domain path computation under domain Uniqueness Constraint
Congress on Evolutionary Computation, 2020Co-Authors: Huynh Thi Thanh Binh, Ta Bao Thangy, Nguyen Binh Long, Ngo Viet Hoang, Pham Dinh ThanhAbstract:Nowadays, connectivity among communication devices in networks has been playing a significant role, especially when the number of devices is increasing dramatically that requires network service providers to have a better architecture of management system. One of the popular approach is to divide those devices inside a network into different domains, in which the problem of minimizing path computation in general or Inter-Domain Path Computation under Domain Uniqueness Constraint (IDPC-DU) problem in specific has received much attention from the research community. Since the IDPC-DU is NP-complete, an approximate approach is usually taken to tackle this problem when the dimensionality is high. Although Multifactorial Evolutionary Algorithm (MFEA) has emerged as an effective approximation algorithm to deal with various fields of problems, there are still some difficulties to apply directly MFEA to solve the IDPC-DU problem, i.e. different chromosomes may have different numbers of genes or to construct a feasible solution not violating the problem’s Constraint. Therefore, to overcome these limitations, MFEA algorithm with a new solution representation based on Priority-based Encoding is introduced. With the new representation of the solution, a chromosome consists of two parts: the first part encodes the priority of the vertex while the second part encodes information of edges in the solution. Besides, the paper also proposed a corresponding decoding method as well as novel crossover and mutation operators. Those evolutionary operators always produce valid solutions. For examining the efficiency of the proposed MFEA, experiments on a wide range of test sets of instances were implemented and the results pointed out the effectiveness of the proposed algorithm. Finally, the characteristics of the proposed algorithm are also indicated and carefully analyzed.
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CEC - Multifactorial Evolutionary Algorithm for Inter-Domain Path Computation under Domain Uniqueness Constraint
2020 IEEE Congress on Evolutionary Computation (CEC), 2020Co-Authors: Huynh Thi Thanh Binh, Ta Bao Thangy, Nguyen Binh Long, Ngo Viet Hoang, Pham Dinh ThanhAbstract:Nowadays, connectivity among communication devices in networks has been playing a significant role, especially when the number of devices is increasing dramatically that requires network service providers to have a better architecture of management system. One of the popular approach is to divide those devices inside a network into different domains, in which the problem of minimizing path computation in general or Inter-Domain Path Computation under Domain Uniqueness Constraint (IDPC-DU) problem in specific has received much attention from the research community. Since the IDPC-DU is NP-complete, an approximate approach is usually taken to tackle this problem when the dimensionality is high. Although Multifactorial Evolutionary Algorithm (MFEA) has emerged as an effective approximation algorithm to deal with various fields of problems, there are still some difficulties to apply directly MFEA to solve the IDPC-DU problem, i.e. different chromosomes may have different numbers of genes or to construct a feasible solution not violating the problem’s Constraint. Therefore, to overcome these limitations, MFEA algorithm with a new solution representation based on Priority-based Encoding is introduced. With the new representation of the solution, a chromosome consists of two parts: the first part encodes the priority of the vertex while the second part encodes information of edges in the solution. Besides, the paper also proposed a corresponding decoding method as well as novel crossover and mutation operators. Those evolutionary operators always produce valid solutions. For examining the efficiency of the proposed MFEA, experiments on a wide range of test sets of instances were implemented and the results pointed out the effectiveness of the proposed algorithm. Finally, the characteristics of the proposed algorithm are also indicated and carefully analyzed.
Huynh Thi Thanh Binh - One of the best experts on this subject based on the ideXlab platform.
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A two-level strategy based on evolutionary algorithm to solve the inter-domain path computation under node-defined domain Uniqueness Constraint
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III, 2021Co-Authors: Anh Do Tuan, Long Nguyen Hoang, Thang Ta Bao, Huynh Thi Thanh BinhAbstract:The Inter-Domain Path Computation problem under Node-defined Domain Uniqueness Constraint (IDPC-NDU) is a recently investigated topic for finding the effective routing paths on the multi-domain network topology as well as transportation. The objective of the IDPC-NDU is to find the shortest path in the multi-domain directed graph that traverses every domain at most once. Since the IDPC-NDU belongs to NP-Hard class, this paper proposes a novel two-level approach based on an Evolutionary Algorithm (EA) to solve it. The first level aims to determine the sequence of crossed domains using an improved Genetic Algorithm (GA), while the second one aims to locate the minimally costly path between two nodes among the entire domains. Furthermore, we devise an approach to represent a chromosome, which reduces the chromosome length to the number of domains. Experiments on numerous sets of instances were implemented to show the effectiveness and characteristics of the proposed algorithm.
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multifactorial evolutionary algorithm for inter domain path computation under domain Uniqueness Constraint
Congress on Evolutionary Computation, 2020Co-Authors: Huynh Thi Thanh Binh, Ta Bao Thangy, Nguyen Binh Long, Ngo Viet Hoang, Pham Dinh ThanhAbstract:Nowadays, connectivity among communication devices in networks has been playing a significant role, especially when the number of devices is increasing dramatically that requires network service providers to have a better architecture of management system. One of the popular approach is to divide those devices inside a network into different domains, in which the problem of minimizing path computation in general or Inter-Domain Path Computation under Domain Uniqueness Constraint (IDPC-DU) problem in specific has received much attention from the research community. Since the IDPC-DU is NP-complete, an approximate approach is usually taken to tackle this problem when the dimensionality is high. Although Multifactorial Evolutionary Algorithm (MFEA) has emerged as an effective approximation algorithm to deal with various fields of problems, there are still some difficulties to apply directly MFEA to solve the IDPC-DU problem, i.e. different chromosomes may have different numbers of genes or to construct a feasible solution not violating the problem’s Constraint. Therefore, to overcome these limitations, MFEA algorithm with a new solution representation based on Priority-based Encoding is introduced. With the new representation of the solution, a chromosome consists of two parts: the first part encodes the priority of the vertex while the second part encodes information of edges in the solution. Besides, the paper also proposed a corresponding decoding method as well as novel crossover and mutation operators. Those evolutionary operators always produce valid solutions. For examining the efficiency of the proposed MFEA, experiments on a wide range of test sets of instances were implemented and the results pointed out the effectiveness of the proposed algorithm. Finally, the characteristics of the proposed algorithm are also indicated and carefully analyzed.
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CEC - Multifactorial Evolutionary Algorithm for Inter-Domain Path Computation under Domain Uniqueness Constraint
2020 IEEE Congress on Evolutionary Computation (CEC), 2020Co-Authors: Huynh Thi Thanh Binh, Ta Bao Thangy, Nguyen Binh Long, Ngo Viet Hoang, Pham Dinh ThanhAbstract:Nowadays, connectivity among communication devices in networks has been playing a significant role, especially when the number of devices is increasing dramatically that requires network service providers to have a better architecture of management system. One of the popular approach is to divide those devices inside a network into different domains, in which the problem of minimizing path computation in general or Inter-Domain Path Computation under Domain Uniqueness Constraint (IDPC-DU) problem in specific has received much attention from the research community. Since the IDPC-DU is NP-complete, an approximate approach is usually taken to tackle this problem when the dimensionality is high. Although Multifactorial Evolutionary Algorithm (MFEA) has emerged as an effective approximation algorithm to deal with various fields of problems, there are still some difficulties to apply directly MFEA to solve the IDPC-DU problem, i.e. different chromosomes may have different numbers of genes or to construct a feasible solution not violating the problem’s Constraint. Therefore, to overcome these limitations, MFEA algorithm with a new solution representation based on Priority-based Encoding is introduced. With the new representation of the solution, a chromosome consists of two parts: the first part encodes the priority of the vertex while the second part encodes information of edges in the solution. Besides, the paper also proposed a corresponding decoding method as well as novel crossover and mutation operators. Those evolutionary operators always produce valid solutions. For examining the efficiency of the proposed MFEA, experiments on a wide range of test sets of instances were implemented and the results pointed out the effectiveness of the proposed algorithm. Finally, the characteristics of the proposed algorithm are also indicated and carefully analyzed.
Long Quan - One of the best experts on this subject based on the ideXlab platform.
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match propagation for image based modeling and rendering
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002Co-Authors: Maxime Lhuillier, Long QuanAbstract:This paper presents a quasi-dense matching algorithm between images based on the match propagation principle. The algorithm starts from a set of sparse seed matches, then propagates to the neighboring pixels by the best-first strategy, and produces a quasi-dense disparity map. The quasi-dense matching aims at broad modeling and visualization applications which rely heavily on matching information. Our algorithm is robust to initial sparse match outliers due to the best-first strategy. It is efficient in time and space as it is only output sensitive. It handles half-occluded areas because of the simultaneous enforcement of newly introduced discrete 2D gradient disparity limit and the Uniqueness Constraint. The properties of the algorithm are discussed and empirically demonstrated. The quality of quasi-dense matching are validated through intensive real examples.
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Match Propagation for Image-Based Modeling and Rendering
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002Co-Authors: Maxime Lhuillier, Long QuanAbstract:This paper presents a quasi-dense matching algorithm between images based on match propagation principle. The algorithm starts from a set of sparse seed matches, then propagates to the neighboring pixels by the best-first strategy, and produces a quasi-dense disparity map. The quasi-dense matching aims at broad modeling and visualization applications which rely heavily on matching information. Our algorithm is robust to initial sparse match outliers due to the best-first strategy; It is efficient in time and space as it is only output sensitive; It handles half-occluded areas because of the simultaneous enforcement of newly introduced discrete 2D gradient disparity limit and the Uniqueness Constraint. The properties of the algorithm are discussed and empirically demonstrated. The quality of quasi-dense matching are validated through intensive real examples.
Christian Jutten - One of the best experts on this subject based on the ideXlab platform.
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Sparse decomposition of two dimensional signals
2009 IEEE International Conference on Acoustics Speech and Signal Processing, 2009Co-Authors: Aboozar Ghaffari, Massoud Babaie-zadeh, Christian JuttenAbstract:In this paper, we consider sparse decomposition (SD) of two-dimensional (2D) signals on overcomplete dictionaries with separable atoms. Although, this problem can be solved by converting it to the SD of one-dimensional (1D) signals, this approach requires a tremendous amount of memory and computational cost. Moreover, the Uniqueness Constraint obtained by this approach is too restricted. Then in the paper, we present an algorithm to be used directly for sparse decomposition of 2D signals on dictionaries with separable atoms. Moreover, we will state another Uniqueness Constraint for this class of decomposition. Our algorithm is obtained by modifying the Smoothed L0 (SL0) algorithm, and hence we call it two-dimensional SL0 (2D-SL0).
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ICASSP - Sparse decomposition of two dimensional signals
2009 IEEE International Conference on Acoustics Speech and Signal Processing, 2009Co-Authors: Aboozar Ghaffari, Massoud Babaie-zadeh, Christian JuttenAbstract:In this paper, we consider sparse decomposition (SD) of two-dimensional (2D) signals on overcomplete dictionaries with separable atoms. Although, this problem can be solved by converting it to the SD of one-dimensional (1D) signals, this approach requires a tremendous amount of memory and computational cost. Moreover, the Uniqueness Constraint obtained by this approach is too restricted. Then in the paper, we present an algorithm to be used directly for sparse decomposition of 2D signals on dictionaries with separable atoms. Moreover, we will state another Uniqueness Constraint for this class of decomposition. Our algorithm is obtained by modifying the Smoothed L0 (SL0) algorithm, and hence we call it two-dimensional SL0 (2D-SL0).
Yiannis Aloimonos - One of the best experts on this subject based on the ideXlab platform.
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Shape and the Stereo Correspondence Problem
International Journal of Computer Vision, 2005Co-Authors: Abhijit S. Ogale, Yiannis AloimonosAbstract:We examine the implications of shape on the process of finding dense correspondence and half-occlusions for a stereo pair of images. The desired property of the disparity map is that it should be a piecewise continuous function which is consistent with the images and which has the minimum number of discontinuities. To zeroth order, piecewise continuity becomes piecewise constancy. Using this approximation, we first discuss an approach for dealing with such a fronto-parallel shapeless world, and the problems involved therein. We then introduce horizontal and vertical slant to create a first order approximation to piecewise continuity. In particular, we emphasize the following geometric fact: a horizontally slanted surface (i.e., having depth variation in the direction of the separation of the two cameras) will appear horizontally stretched in one image as compared to the other image. Thus, while corresponding two images, N pixels on a scanline in one image may correspond to a different number of pixels M in the other image. This leads to three important modifications to existing stereo algorithms: (a) due to unequal sampling, existing intensity matching metrics must be modified, (b) unequal numbers of pixels in the two images must be allowed to correspond to each other, and (c) the Uniqueness Constraint, which is often used for detecting occlusions, must be changed to an interval Uniqueness Constraint. We also discuss the asymmetry between vertical and horizontal slant, and the central role of non-horizontal edges in the context of vertical slant. Using experiments, we discuss cases where existing algorithms fail, and how the incorporation of these new Constraints provides correct results.
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CVPR (1) - Stereo correspondence with slanted surfaces: critical implications of horizontal slant
Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2004. CVPR 2004., 2004Co-Authors: Abhijit Ogale, Yiannis AloimonosAbstract:We examine the stereo correspondence problem in the presence of slanted scene surfaces. In particular we highlight a previously overlooked geometric fact: a horizontally slanted surface (i.e. having depth variation in the direction of the separation of the two cameras) will appear horizontally stretched in one image as compared to the other image. Thus, while corresponding two images, N pixels on a scanline in one image may correspond to a different number of pixels M in the other image. This leads to three important modifications to existing stereo algorithms: (a) due to unequal sampling, intensity matching metrics such as the popular Birchfield-Tomasi procedure must be modified, (b) unequal numbers of pixels in the two images must be allowed to correspond to each other, and (c) the Uniqueness Constraint, which is often used for detecting occlusions, must be changed to a 3D Uniqueness Constraint. This paper discusses these new Constraints and provides a simple scanline based matching algorithm for illustration. We experimentally demonstrate test cases where existing algorithms fail, and how the incorporation of these new Constraints provides correct results. Experimental comparisons of the scanline based algorithm with standard data sets are also provided.
