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Salient Color Names for Person Re-identification
Yang Yang1, Jimei Yang2, Junjie Yan1, Shengcai Liao1, Dong Yi1, and Stan Z. Li1
1Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
yang.yang@nlpr.ia.ac.cn
jjyan@nlpr.ia.ac.cn
scliao@nlpr.ia.ac.cn
dong.yi@nlpr.ia.ac.cn
szli@nlpr.ia.ac.cn
2University of California, Merced, USA
jyang44@ucmerced.edu
Abstract. Color naming, which relates colors with color names, can help people with a semantic analysis of images in many computer vision applications. In this paper, we propose a novel salient color names based color descriptor (SCNCD) to describe colors. SCNCD utilizes salient color names to guarantee that a higher probability will be assigned to the color name which is nearer to the color. Based on SCNCD, color distributions over color names in different color spaces are then obtained and fused to generate a feature representation. Moreover, the effect of background information is employed and analyzed for person re-identification. With a simple metric learning method, the proposed approach outperforms the state-of-the-art performance (without user’s feedback optimization) on two challenging datasets (VIPeR and PRID 450S). More importantly, the proposed feature can be obtained very fast if we compute SCNCD of each color in advance.
Keywords: Salient color names, color descriptor, feature representation, person re-identification
LNCS 8689, p. 536 ff.
lncs@springer.com
© Springer International Publishing Switzerland 2014