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http://dx.doi.org/10.9717/kmms.2016.19.10.1782

Color Space Exploration and Fusion for Person Re-identification  

Nam, Young-Ho (Dept. of Computer Science in Gyeongsang National Univ. Engineering Research Institute)
Kim, Min-Ki (Dept. of Computer Science in Gyeongsang National Univ. Engineering Research Institute)
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Abstract
Various color spaces such as RGB, HSV, log-chromaticity have been used in the field of person re-identification. However, not enough studies have been done to find suitable color space for the re-identification. This paper reviews color invariance of color spaces by diagonal model and explores the suitability of each color space in the application of person re-identification. It also proposes a method for person re-identification based on a histogram refinement technique and some fusion strategies of color spaces. Two public datasets (ALOI and ImageLab) were used for the suitability test on color space and the ImageLab dataset was used for evaluating the feasibility of the proposed method for person re-identification. Experimental results show that RGB and HSV are more suitable for the re-identification problem than other color spaces such as normalized RGB and log-chromaticity. The cumulative recognition rates up to the third rank under RGB and HSV were 79.3% and 83.6% respectively. Furthermore, the fusion strategy using max score showed performance improvement of 16% or more. These results show that the proposed method is more effective than some other methods that use single color space in person re-identification.
Keywords
Color Space; Fusion; Person Re-identification;
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