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http://dx.doi.org/10.14372/IEMEK.2013.8.2.121

Efficient Implementation of Candidate Region Extractor for Pedestrian Detection System with Stereo Camera based on GP-GPU  

Jeong, Geun-Yong (Incheon University)
Jeong, Jun-Hee (Incheon University)
Lee, Hee-Chul (Incheon University)
Jeon, Gwang-Gil (Incheon University)
Cho, Joong-Hwee (Incheon University)
Publication Information
IEMEK Journal of Embedded Systems and Applications / v.8, no.2, 2013 , pp. 121-128 More about this Journal
Abstract
There have been various research efforts for pedestrian recognition in embedded imaging systems. However, many suffer from their heavy computational complexities. SVM classification method has been widely used for pedestrian recognition. The reduction of candidate region is crucial for low-complexity scheme. In this paper, We propose a real time HOG based pedestrian detection system on GPU which images are captured by a pair of cameras. To speed up humans on road detection, the proposed method reduces a number of detection windows with disparity-search and near-search algorithm and uses the GPU and the NVIDIA CUDA framework. This method can be achieved speedups of 20% or more compared to the recent GPU implementations. The effectiveness of our algorithm is demonstrated in terms of the processing time and the detection performance.
Keywords
Pedestrian detection; HOG; SVM; Sterero camera; Candidate region; Disparity-base search; Near-search; Support vector machine; GPU;
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