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Optimized parallel implementation of pedestrian tracking using HOG features on GPU

H. Sugano, R. Miyamoto, Y. Nakamura
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}

}

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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.
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