Abstract
Person re-identification obtains a major concern from researchers owing to its extensive applications and many challenges. Feature extraction is the first step for person re-identification, and a robust feature can promote the performance. In this paper, we mainly introduce channel-based and region-based feature representation methods and evaluate several representative features that combine the two above-mentioned methods on the VIPeR database.
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Acknowledgements
This work is supported by National Natural Science Foundation of China under Grant No. 61711530240, No. 61501327 and No. 61401309, Natural Science Foundation of Tianjin under Grant No. 17JCZDJC30600, and No. 15JCQNJC01700, the Open Projects Program of National Laboratory of Pattern Recognition under Grant No. 201700001, and Doctoral Fund of Tianjin Normal University under Grant No. 5RL134 and No. 52XB1405.
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Zhang, Z., Huang, M., Liu, S., Durrani, T.S. (2019). Evaluation Hand-Craft Features for Person Re-identification. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_273
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DOI: https://doi.org/10.1007/978-981-10-6571-2_273
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