Abstract:Person re-identification, identifying the same person’s images in an existing database come from non-overlapping camera views, is a valuable but challenging task. This paper proposes a statistical inference approach for person re-identification. A similarity measure of two person images is learned from a statistical inference perspective. Then the similarity measure is utilized to query a person from a gallery set. The proposed approach is demonstrated on VIPeR dataset, and the experiment shows that it outperforms the state-of-the-art approaches. Besides, it costs less time than the existing learning-based ones in training, and alleviates the over-fitting problem when there are few training data.
杜宇宁, 艾海舟. 基于统计推断的行人再识别算法[J]. 电子与信息学报, 2014, 36(7): 1612-1618.
Du Yu-Ning, Ai Hai-Zhou. A Statistical Inference Approach for Person Re-identification. , 2014, 36(7): 1612-1618.