Abstract
Pedestrian detection is a specific application of object detection. Compared with general object detection, it shows similarities and unique characteristics. In addition, it has important application value in the fields of intelligent driving and security monitoring. In recent years, with the rapid development of deep learning, pedestrian detection technology has also made great progress. However, there still exists a huge gap between it and human perception. Meanwhile, there are still a lot of problems, and there remains a lot of room for research. Regarding the application of pedestrian detection in intelligent driving technology, it is of necessity to ensure its real-time performance. Additionally, it is necessary to lighten the model while ensuring detection accuracy. This paper first briefly describes the development process of pedestrian detection and then concentrates on summarizing the research results of pedestrian detection technology in the deep learning stage. Subsequently, by summarizing the pedestrian detection dataset and evaluation criteria, the core issues of the current development of pedestrian detection are analyzed. Finally, the next possible development direction of pedestrian detection technology is explained at the end of the paper.
Highlights
Object detection is a basic problem of machine vision and deep learning, and it lays the basis for the in-depth development of numerous research problems, including instance segmentation [1,2,3], object tracking and optimization [4,5,6], trajectory prediction [7], and image reconstruction [8,9,10]
As a typical object detection task, pedestrian detection has a special position in fields such as intelligent driving, and it is directly related to driving safety and pedestrian safety
Is review first introduces the content of general object detection, analyzes the development of pedestrian detection, and elaborates on the common datasets and main problems faced by pedestrian detection
Summary
Object detection is a basic problem of machine vision and deep learning, and it lays the basis for the in-depth development of numerous research problems, including instance segmentation [1,2,3], object tracking and optimization [4,5,6], trajectory prediction [7], and image reconstruction [8,9,10]. Pedestrian detection is a specific application of the object detection problem, and it has become one of the research hotspots in recent years. It has important application value in the fields of intelligent driving and security monitoring. Compared with other types of object detection, pedestrian detection puts forward stricter requirements on accuracy and realtime performance, which is of extraordinary significance in the field of intelligent driving. Large quantities of reviews of general object detection have been published [24,25,26,27,28], but there are few reviews of pedestrian detection, lacking the analysis of its latest developments and discussion of current difficulties. By performing a rough analysis of general object detection, this paper will discuss in-depth pedestrian detection
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