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Proceedings Paper

A new algorithm for pedestrian detection
Author(s): Ke-yang Cheng; Jun-xian Bao
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Paper Abstract

This article puts forward a novel framework for pedestrian detection tasks, which proposing a model with both sparse reconstruction and class discrimination components, jointly optimized during dictionary learning. We present an efficient pedestrian detection system using mixing sparse features of HOG, FOG and CSS to combine into a Kernel classifier. Results presented on our data set show competitive accuracy and robust performance of our system outperforms current state-of-the-art work.

Paper Details

Date Published: 19 July 2013
PDF: 7 pages
Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88783C (19 July 2013); doi: 10.1117/12.2031762
Show Author Affiliations
Ke-yang Cheng, Nanjing Univ. of Aeronautics and Astronautics (China)
Jiangsu Univ. (China)
Jun-xian Bao, Jiangsu Univ. (China)


Published in SPIE Proceedings Vol. 8878:
Fifth International Conference on Digital Image Processing (ICDIP 2013)
Yulin Wang; Xie Yi, Editor(s)

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