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Proceedings Paper

An applied study of human detection in single images
Author(s): Ren Liu; Xianghua Xie
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Paper Abstract

In this paper we perform an applied comparative study of popular HOG based human detection and a state-of-the-art pose adaptive method that uses shape-based model construction. Both methods are implemented with kernel SVM, instead of linear SVM. Detailed performance evaluation is carried out on MIT pedestrian dataset and INRIA person dataset. This study shows that, although pose adaptive method has no significant advantage compared to the HOG based approach on those datasets, the pose adaptive approach is more efficient in detection and it has the capability to segment the human shape from images while carrying out detection which can be advantageous in many applications.

Paper Details

Date Published: 15 November 2011
PDF: 9 pages
Proc. SPIE 8335, 2012 International Workshop on Image Processing and Optical Engineering, 83350D (15 November 2011); doi: 10.1117/12.917683
Show Author Affiliations
Ren Liu, Swansea Univ. (United Kingdom)
Xianghua Xie, Swansea Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 8335:
2012 International Workshop on Image Processing and Optical Engineering
Hai Guo; Qun Ding, Editor(s)

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