Optimized parallel implementation of pedestrian tracking using HOG features on GPU
Dept. of Comm. & Comput. Eng., Kyoto Univ., Kyoto, Japan
Conference on Ph.D. Research in Microelectronics and Electronics (PRIME), 2010
@inproceedings{sugano2010optimized,
title={Optimized parallel implementation of pedestrian tracking using HOG features on GPU},
author={Sugano, H. and Miyamoto, R. and Nakamura, Y.},
booktitle={Ph. D. Research in Microelectronics and Electronics (PRIME), 2010 Conference on},
pages={1–4},
organization={IEEE},
year={2010}
}
Accurate pedestrian recognition is required for practical applications such as automotive and security applications. To improve accuracy of recognition, accurate tracking is indispensable just as detection. The authors proposed a novel accurate tracking scheme using HOG features and its parallel implementation on GPU aiming real-time processing. However, the implementation does not have enough performance because the optimization is not sufficient. In this paper, we propose optimized implementation of HOG-based pedestrian tracking on GPU. By the proposed implementation, the total processing speed becomes 2.6 times faster than that of original one and real-time processing is achieved.
May 17, 2011 by hgpu
