Efficient HOG human detection

Pang, Y. and Yuan, Y. and Li, Xuelong and Pan, J. (2011) Efficient HOG human detection. Signal Processing 91 (4), pp. 773-781. ISSN 0165-1684.

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Official URL: http://dx.doi.org/10.1016/j.sigpro.2010.08.010

Abstract

While Histograms of Oriented Gradients (HOG) plus Support Vector Machine (SVM) (HOG+SVM) is the most successful human detection algorithm, it is time-consuming. This paper proposes two ways to deal with this problem. One way is to reuse the features in blocks to construct the HOG features for intersecting detection windows. Another way is to utilize sub-cell based interpolation to efficiently compute the HOG features for each block. The combination of the two ways results in significant increase in detecting humans—more than five times better. To evaluate the proposed method, we have established a top-view human database. Experimental results on the top-view database and the well-known INRIA data set have demonstrated the effectiveness and efficiency of the proposed method.

Metadata

Item Type:	Article
Keyword(s) / Subject(s):	image and video processing, human detection, HOG, fast algorithm
School:	Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Depositing User:	Sarah Hall
Date Deposited:	20 Jun 2013 09:45
Last Modified:	09 Aug 2023 12:33
URI:	https://eprints.bbk.ac.uk/id/eprint/7514

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