A survey on people re-identification approaches considering occlusion

Analyzing human behavior and detecting visual anomaly are important applications of video surveillance systems in many fields such as security systems and intelligent buildings. Person re-identification (RE-ID) is one of the main steps in a surveillance system, where, it has directly an effect on system performance. Occluded body parts, backgrounds clutter, and variations in pose and scene illumination are some noticeable problems in appearance-based RE-ID approaches, as they have an effect on pedestrians’ appearance during tracking task. Among the mentioned problems, person RE-ID considering appearance changes caused by occlusion can be considered as a common problem in video surveillance systems. In this paper, some existing people RE-ID approaches are briefly reviewed in terms of robustness to person body occlusion. Also, the experimental results reported in these approaches are compared using some partial occluded databases. The comparison results demonstrate the supremacy of the non-pose-guided RE-ID approaches.