Optimized parallel implementation of pedestrian tracking using HOG features on GPU
Hiroki Sugano, Ryusuke Miyamoto, Yukihiro Nakamura · Conference on Ph.D. Research in Microelectronics and Electronics · 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.