Abstract:

Pedestrian detection has been widely applied in intelligent traffic, intelligent monitoring, unmanned driving, pedestrian analysis and other fields. With the development of technology, the accuracy of pedestrian detection technology has become increasingly high. This paper summarizes the research progress of pedestrian detection technology under occlusion. Firstly, according to different occlusion, it can be divided into reasonable-occlusion caused by non-target and reasonable-crowd caused by target to be detected. Secondly, this paper summarizes the traditional method and deep learning method to deal with occlusion. The main ideas and core problems of each method model are analyzed and discussed. Finally, this paper gives an outlook on the problems to be solved in the future development of pedestrian detection technology under occlusion.

Key words: occlusion pedestrian detection, neural network, artificial features, deep learning

摘要：

行人检测在智能交通、智能监控、无人驾驶、行人分析等领域都有广泛应用，随着技术发展，对行人检测技术的精度要求也越来越高。对遮挡情况下的行人检测技术进行了研究，根据遮挡物的不同，将遮挡分为非目标造成的遮挡及需要检测的目标造成的遮挡。分别总结了处理遮挡情况的传统方法和深度学习方法，并对每一类方法模型的主要思想和核心问题进行了分析和讨论。对遮挡下的行人检测技术在未来发展中亟待解决的问题提出展望。

关键词: 遮挡行人检测, 神经网络, 人工特征, 深度学习