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CVPR
2007
IEEE

Pedestrian Detection in Infrared Images based on Local Shape Features

13 years 10 months ago
Pedestrian Detection in Infrared Images based on Local Shape Features
Use of IR images is advantageous for many surveillance applications where the systems must operate around the clock and external illumination is not always available. We investigate the methods derived from visible spectrum analysis for the task of human detection. Two feature classes (edgelets and HOG features) and two classification models(AdaBoost and SVM cascade) are extended to IR images. We find out that it is possible to get detection performance in IR images that is comparable to state-of-the-art results for visible spectrum images. It is also shown that the two domains share many features, likely originating from the silhouettes, in spite of the starkly different appearances of the two modalities.
Li Zhang, Bo Wu, Ram Nevatia
Added 02 Jun 2010
Updated 02 Jun 2010
Type Conference
Year 2007
Where CVPR
Authors Li Zhang, Bo Wu, Ram Nevatia
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