Zenithal Pedestrian Detection Based on Histogram of Oriented Gradient
TANG Chun-Hui
Engineering Research Center of Optical Instrument and System of Ministry of Education,School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093 Shanghai Key Laboratory of Modern Optical System, School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology, Shanghai 200093
Abstract There are extensive researches on pedestrian detection, which mostly suppose visible humans observed in flat view and are applied in video surveillance,driving assistance etc. However, sometimes pedestrian detection from another perspective should be considered in practice. In this paper, a histogram of oriented gradients (HOG) descriptor is introduced for the zenithal pedestrian head detection. The vectors extracted from training samples are trained in the support vector machine to get the classifier parameters, and then the vectors of test samples are input into the classifier to discriminate which targets are. Compared with the existing methods, the proposed descriptor highlights both the region and the contour of the object. Partitioning blocks are reformed, and the feature calculation and statistical method are changed adaptively to the task. The experimental results show that the proposed method is effective and can be applied to count pedestrians in vertical view with a faster processing speed.
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2015, Vol. 28 
