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http://dx.doi.org/10.13089/JKIISC.2011.21.6.161

Multicore Processor based Parallel SVM for Video Surveillance System  

Kim, Hee-Gon (Korea University)
Lee, Sung-Ju (Korea University)
Chung, Yong-Wha (Korea University)
Park, Dai-Hee (Korea University)
Lee, Han-Sung (ETRI)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.21, no.6, 2011 , pp. 161-169 More about this Journal
Abstract
Recent intelligent video surveillance system asks for development of more advanced technology for analysis and recognition of video data. Especially, machine learning algorithm such as Support Vector Machine (SVM) is used in order to recognize objects in video. Because SVM training demands massive amount of computation, parallel processing technique is necessary to reduce the execution time effectively. In this paper, we propose a parallel processing method of SVM training with a multi-core processor. The results of parallel SVM on a 4-core processor show that our proposed method can reduce the execution time of the sequential training by a factor of 2.5.
Keywords
Video Surveillance Applications; SVM; Parallel Processing; Multi-core;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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