Stereo-based Pedestrian Detection Using Two-stage Classifiers
نویسندگان
چکیده
Detecting pedestrians from a moving vehicle is a challenging problem since the essence of the task is to search non-rigid moving objects with various appearances in a dynamic and outdoor environment. In order to alleviate these difficulties, we basically use Co-occurrence Histograms of Oriented Gradients (CoHOG) as a feature descriptor. While the CoHOG feature provides high classification performance, it requires a high computational cost. In this paper we introduce another combination of a feature descriptor and a classifier for the first stage operation in order to reduce computational cost. Through experiments we show that the proposed method can reduce the calculation time while keeping the pedestrian detection capability.
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