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Detecting Pedestrians Using An Advanced Local Binary Pattern Histogram

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Yunyun Cao, Hirofumi Nishimura, Sugiri Pranata
18th ITS World Congress, Orlando, USA, 16-20 October, 2011

Fast and simple for implementation, Local binary pattern (LBP), has shown its superiority in texture classification and face recognition, but weak in pedestrian recognition. An enhanced LBP Feature — Weighted LBP Histogram, is proposed for robust pedestrian detection. In Weighted LBP Histogram, each bin value is calculated by accumulating the weight of each pixel s LBP code which belongs to this bin, whereas the weight is defined as the Sum of Absolute Difference (SAD) of the centre pixel and its surrounding pixels. The experimental results show its effectiveness on alleviation of noise and enhancement of signal-to-noise ratio. Utilizing the proposed LBP feature, our pedestrian detection system achieves a high performance than the benchmark method HOG on several benchmark datasets.

Link: https://itswc.confex.com/itswc/WC2011/webprogram/Paper2791.html