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Statistical layout of improved image descriptor for pedestrian detection
Bai M(白明); Zhuang Y(庄严); Wang W(王伟)
Department机器人学研究室
Source PublicationICIC Express Letters
ISSN1881-803X
2010
Volume4Issue:5 BPages:1931-1936
Indexed ByEI
EI Accession number20103913254454
Contribution Rank1
AbstractAn automatic and robust approach for pedestrian detection is proposed in natural scene images, even in the presence of clutter and occlusion. An improved statistical descriptor is designed to encode more support vectors, and the dimensionality reduction method compactly optimizes it without its performance degradation. To improve the efficiency, similarity measurement kernel adopts a pyramid matching mode, and the statistic multi-models detector significantly improves the performance on challenging scenes. Comparisons in various aspects validate that the improved descriptor is more distinctive and robust, which results in a higher discriminant performance and a better efficiency. The experimental results testify the effectivity and robustness of pedestrian detection in complicated scene images.
Language英语
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/19916
Collection机器人学研究室
Corresponding AuthorBai M(白明)
Affiliation1.Research Center of Information and Control, Dalian University of Technology, Dalian 116024, China
2.State Key Laboratory of Robotics, Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
Recommended Citation
GB/T 7714
Bai M,Zhuang Y,Wang W. Statistical layout of improved image descriptor for pedestrian detection[J]. ICIC Express Letters,2010,4(5 B):1931-1936.
APA Bai M,Zhuang Y,&Wang W.(2010).Statistical layout of improved image descriptor for pedestrian detection.ICIC Express Letters,4(5 B),1931-1936.
MLA Bai M,et al."Statistical layout of improved image descriptor for pedestrian detection".ICIC Express Letters 4.5 B(2010):1931-1936.
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