PDF
Full
Outline
The purpose of this research is to clarify the research progress of the theory and technology of pedestrian abnormal behavior recognition in public places. Firstly，with the help of China National Knowledge Infrastructure (CNKI) and the Web of Science (WOS)，a broad definition and universal characteristics of abnormal pedestrian behavior in public places were given. The existing research results related to abnormal behaviors were divided into three categories: harmful behaviors，dissociable behaviors and violations. Then，from the perspective of data and technological foundations，the existing abnormal behavior recognition methods were divided into four categories: artificial design，human skeleton，Red Geen Blue(RGB) images and wearable sensors. Secondly，this study sorted out the abnormal behavior datasets of mainstream populations both domestically and internationally，and analyzed the performance of relevant algorithms on the datasets. Finally，the limitations of existing research methods in available datasets and data fusion detection were summarized，and future research directions and optimization suggestions were provided. The results indicate that these four types of abnormal behavior recognition methods have their own advantages and disadvantages. It is necessary to construct a diversified，well-defined and high-quality international benchmark dataset of abnormal behaviors among the crowd. Future research should focus on robust and accurate methods，models，and algorithms for identifying abnormal behaviors，explore multi-dimensional data fusion complementary detection methods，improve the application scenario consistency and adaptability of the theoretical results of abnormal behavior recognition，and eventually enhance the level of public place crowd safety governance.
PDF
384
166
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62199257
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
