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    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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    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: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 20 Jun 2013 09:45
    Last Modified: 11 Oct 2016 15:27
    URI: https://eprints.bbk.ac.uk/id/eprint/7514

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