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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
People detection in low resolution infrared videos
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Roland Miezianko, Honeywell Labs, Minneapolis, 55418, USA
Dragoljub Pokrajac, Delaware State University, Dover, 19901, USA
In this paper we present a method for detecting people in low resolution infrared videos. We further explore the feature set based on histogram of gradients beyond the well received HOG descriptors. Our approach is based on extracting gradient histograms from recursively generated patches and subsequently computing histogram ratios between the patches. Each set of patches is defined in terms of relative position within the search window, and each set is then recursively applied to extract smaller patches. The histogram of gradient ratios between patches become the feature vector. We adopted a linear SVM classifier as it provides a fast and effective framework for feature descriptor processing with minimal parameter tuning. Experimental results are presented on various OTCBVS datasets.
Citation:
Roland Miezianko, Dragoljub Pokrajac, "People detection in low resolution infrared videos," cvprw, pp.1-6, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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