Survey of pedestrian detection with occlusion
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SURVEY AND STATE OF THE ART
Survey of pedestrian detection with occlusion Chen Ning1
· Li Menglu1 · Yuan Hao1 · Su Xueping1 · Li Yunhong1
Received: 7 March 2020 / Accepted: 22 September 2020 © The Author(s) 2020
Abstract Pedestrian detection is widely applied in surveillance, autonomous robotic navigation, and automotive safety. However, there are many occlusion problems in real life. This paper summarizes the research progress of pedestrian detection technology with occlusion. First, according to different occlusion, it can be divided into two categories: inter-class occlusion and intra-class occlusion. Second, it summarizes the traditional method and deep learning method to deal with occlusion. Furthermore, the main ideas and core problems of each method model are analyzed and discussed. Finally, the paper gives an outlook on the problems to be solved in the future development of pedestrian detection technology with occlusion. Keywords Occlusion pedestrian detection · Neural network · Artificial features · Deep learning
Introduction
Motivation
Pedestrian detection technology is a computer for the given video and image, to determine it is pedestrians, and mark the location of pedestrians. The rapid development of artificial intelligence technology also makes pedestrian detection set off a new upsurge in the field of computer vision. Pedestrian detection provides technical support and foundation for gait analysis, pedestrian identification, pedestrian analysis. These technologies are widely applied in video surveillance [1–4], self-driving cars [5–8], autonomous robots [9, 10] and many other fields. The pedestrian detection technology has been advancing continuously in the past ten years. However, there is still a big problem to solve the occlusion situation. According to a recent survey, in a video that taken by a street, at least 70% [11] of pedestrians are occluded in Banks, shops, railway stations, and airports. The interference of complex background or other objects can increase the difficulty of pedestrian detection. At the same time, the commercial pedestrian detection system put forward high demands to overcome challenges.
Pedestrian detection under occlusion has been widely used in the field of smart city. For example, vehicle-assisted driving systems, intelligent video surveillance, robotics, human— computer interaction systems, and security work all benefit from occluded pedestrian detection. In the field of intelligent transportation, assisted driving and autonomous driving are two important directions. Pedestrian detection under occlusion is one of the important foundations of the above directions. Accurate pedestrian detection under occlusion can help drivers to locate pedestrians and timely remind drivers to give way to people. At the same time, the detection results are helpful to risk management of driving behavior and improve driving safety. This has been playing an important role in ensuring the traffic safety of modern urban. In the field of security, it has become an important task to f
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