Invariance Matters: Person Re-identification by Local Color Transfer

Ying Niu, Chunmiao Yuan, Kunliang Liu, Yukuan Sun, Jiayu Liang, Guanghao Jin, Jianming Wang

Abstract: Person re-identification is a complex image retrieval problem. The color of the image is distorted due to changes in illumination, etc., which makes pedestrian recognition more challenging. In this paper, we take the conditional image, the reference image and its corresponding clothing segmentation image as input, and then restore the true color of the person through color conversion. In addition, we calculate the similarity between the conditional image and the image dataset by the chromatic aberration similarity and the clothing segmentation invariance. We evaluated the proposed method on a public dataset. A large number of experimental results show that the method is effective.

External IDs:dblp:conf/adma/NiuYLSLJW19