Only few problems in computer vision have been investigated more vigorously than stereo. Nevertheless, the main obstacle on the way to their practical application is the excessively long computation time needed to mat...
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Only few problems in computer vision have been investigated more vigorously than stereo. Nevertheless, the main obstacle on the way to their practical application is the excessively long computation time needed to match stereo images. This paper presents parallel algorithms for edge-based stereo suitable for depth computation. Edge-based stereo techniques produce only sparse depth maps. Thus, we present in addition an efficient parallel algorithm for dense stereo matching that can be employed in scene reconstruction. Both approaches are implemented on several different computers to measure the performance. We compared single processor and multiple processor implementations to evaluate the profit of parallel realizations. Results are presented in this paper. We show that both approaches are very suitable for parallel implementations and that computing time can be considerably reduced with parallel implementations. Furthermore, we present the results that are obtained when employing the different approaches to stereo images.
Given N matrices A1, A2,..., AN of size NxN, the matrix chain product problem is to compute A1 x A2 xx AN. Given an N x N matrix A, the matrix powers problem is to calculate the first N powers of A, i.e., A, A2, A3,.....
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This paper presents a simple to use and general approach for designing efficient parallel algorithms for distributed memory machines. This approach is well suited for solving both regular and irregular problems using ...
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Three parallel algorithms for the eigensolution of real symmetric matrices of order n on a SIMD-type parallel computer with an associative memory are considered. The algorithms realize various parallel orderings of th...
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In this paper we report on three parallel algorithms used for 3D reconstruction of asymmetric objects from their 2D projections. We discuss their computational, communication, I/O, and space requirements and present s...
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In this paper, we present efficient parallel algorithms for solving several fundamental problems on planar st-graphs. The problems we consider include all-pairs shortest paths in weighted planar st-graphs, single-sour...
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In this paper we have developed algorithms to solve macroeconometric models with forward-looking variables based on Newton method for nonlinear systems of equations. The most difficult step for Newton methods represen...
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In this paper we have developed algorithms to solve macroeconometric models with forward-looking variables based on Newton method for nonlinear systems of equations. The most difficult step for Newton methods represents the resolution of a large linear system for each iteration. Thus, we compare the performances resulted by solving this linear system using two iterative methods and the direct method. We’ve also described an implementation of the parallel versions of such algorithms using a software package. Our experiments confirm that the iterative methods have a low computational complexity and storage requirements, but the parallel versions of direct methods show a superior speedup.
This paper presents a comparison of the pragmatic aspects of some parallel algorithms for finding connected components, together with optimizations on these algorithms. The algorithms being compared are two similar al...
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The cost of interprocessor communication has a substantial impact on execution time when implementating parallel algorithms on physical parallel computers. We study these implementation costs, examining the number of ...
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The cost of interprocessor communication has a substantial impact on execution time when implementating parallel algorithms on physical parallel computers. We study these implementation costs, examining the number of inter-processor messages, the cost of routing these messages on various architectures, and the number of communication phases. We provide an improved direct routing algorithm for realizing h-relations on crossbar networks. We also introduce a round-robin message-delivery algorithm which reduces the number of times a communication link is established between a pair of processors (by delivering all messages of that phase for the pair in order without interruption.) We summarize criteria sufficient for a parallel algorithm to be implemented optimally on several common networks. We also describe a log n-phase optimal parallel list-ranking algorithm.
The distance transform (DT) and the medial axis transform (MAT) are two important image operations. They are both used to extract of the information about the shape and the position of the foreground pixels relative t...
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The distance transform (DT) and the medial axis transform (MAT) are two important image operations. They are both used to extract of the information about the shape and the position of the foreground pixels relative to each other. Many applications of these transforms are applied in the fields of image processing and computer vision, such as expanding shrinking, thinning and computing shape factor, etc. Each of these two transforms is essentially a global operation. Unless the digital image is very small, all global operations are prohibitively costly. In order to provide the efficient transform computations, it is considerably desired to develop parallel algorithms for these two operations. In this paper, we provide the fastest parallel algorithms to compute the chessboard distance transform (CDT) which is a DT based on the chessboard metrics, and the medial axis transform (MAT). Each of the transforms of a 2-D binary image array of size N×N can be computed in O(1) time on the 2-D 2N×2N RAP.
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