Multiple Pedestrian Tracking Under Occlusion: A Survey and Outlook

Abstract

As an intermediate task in computer vision, multiple pedestrian tracking (MPT) aiming at tracking the pedestrians from a given video, has attracted attention due to its potential academic and commercial value. However, pedestrians commonly suffer from occlusion due to diverse and complex scenarios, which increases the challenge of this task. This survey provides comprehensive review in terms of occlusion scenarios encountered during MPT, and investigates the model robustness of the existing methods in this scenarios. Firstly, this survey introduces the various and states of occlusion. Secondly, the related occlusion datasets are introduced. Subsequently, we categorize existing occlusion handling methods according to the tracking process and detail their pros and cons. In addition, occlusion handling precision (OHP) metric is proposed to evaluate the ability of a tracker in handling occlusion in this survey. Moreover, comprehensive analyzes and discussions in several public datasets are provided to verify the effectiveness of these methods. Finally, the existing issues and future directions for occlusion handling methods are discussed. In doing so, this work serves as a foundation for future research by providing researchers with information about the occlusion handling method of MPT.