Parallelized Random Walk algorithm for background substitution on a multi-core embedded platform

Random Walk (RW) is a popular algorithm and can be applied to many applications in computer vision. In this paper, a fast algorithm is proposed to solve the large linear system in RW based on adapting the Gauss-Seidel method on a multi-core embedded system. Two tables, TYPE and INDEX, are introduced...

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Bibliographic Details
Published in2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 1621 - 1624
Main Authors Yutzu Lee, Chen-Kuo Chiang, Yu-Wei Sun, Te-Feng Su, Shang-Hong Lai
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2012
Subjects
Arrays
background substitution
Digital signal processing
Embedded systems
Image segmentation
Indexes
Linear systems
multi-core embedded system
Multicore processing
parallelization
Random walk
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Summary:Random Walk (RW) is a popular algorithm and can be applied to many applications in computer vision. In this paper, a fast algorithm is proposed to solve the large linear system in RW based on adapting the Gauss-Seidel method on a multi-core embedded system. Two tables, TYPE and INDEX, are introduced to fast locate the required data for the close-form solution. The computational overhead, along with the memory requirement, to solve the linear system can be reduced greatly, thus making the RW algorithm feasible to many applications on an embedded system. In addition, the proposed fast method is parallelized for a heterogeneous multi-core embedded platform to make the most use of the benefits of the system architecture. Experimental results show that the computational overhead can be significantly reduced by the proposed algorithm.
ISBN:1467300454
9781467300452
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2012.6288205