Mechanical Engineering Science

A Review of Research on Person Re-identification in Surveillance Video

ZHANGYunzuo (School of Information science and Technology, Shijiazhuang Tiedao University), LIANWeiqi (School of Information science and Technology, Shijiazhuang Tiedao University)

Abstract


Person re-identification has emerged as a hotspot for computer vision research due to the growing demands of social public safety requirements and the quick development of intelligent surveillance networks. Person re-identification (Re-ID) in video surveillance system can track and identify suspicious people, track and statistically analyze persons. The purpose of person re-identification is to recognize the same person in different cameras. Deep learning-based person re-identification research has produced numerous remarkable outcomes as a result of deep learning's growing popularity. The purpose of this paper is to help researchers better understand where person re-identification research is at the moment and where it is headed. Firstly, this paper arranges the widely used datasets and assessment criteria in person re-identification and reviews the pertinent research on deep learning-based person re-identification techniques conducted in the last several years. Then, the commonly used method techniques are also discussed from four aspects: appearance features, metric learning, local features, and adversarial learning. Finally, future research directions in the field of person re-identification are outlooked.

Keywords


Person re-identification; Deep learning; Metric learning; Local features; Adversarial learning

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DOI: https://doi.org/10.33142/mes.v5i2.12716

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