Effective Crowd Anomaly Detection Through Spatio-temporal Texture Analysis
文献类型：期刊论文
| 作者 | Yu Hao2,3 ; Zhi-Jie Xu2; Ying Liu3; Jing Wang1; Jiu-Lun Fan3
|
| 刊名 | International Journal of Automation and Computing
 |
| 出版日期 | 2019 |
| 卷号 | 16期号:1页码:27-39 |
| 关键词 | Crowd behavior spatial-temporal texture gray level co-occurrence matrix information entropy. |
| ISSN号 | 1476-8186 |
| DOI | 10.1007/s11633-018-1141-z |
| 英文摘要 | Abnormal crowd behaviors in high density situations can pose great danger to public safety. Despite the extensive installation of closed-circuit television (CCTV) cameras, it is still difficult to achieve real-time alerts and automated responses from current systems. Two major breakthroughs have been reported in this research. Firstly, a spatial-temporal texture extraction algorithm is developed. This algorithm is able to effectively extract video textures with abundant crowd motion details. It is through adopting Gabor-filtered textures with the highest information entropy values. Secondly, a novel scheme for defining crowd motion patterns (signatures) is devised to identify abnormal behaviors in the crowd by employing an enhanced gray level co-occurrence matrix model. In the experiments, various classic classifiers are utilized to benchmark the performance of the proposed method. The results obtained exhibit detection and accuracy rates which are, overall, superior to other techniques. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/42319]  |
| 专题 | 自动化研究所_学术期刊_International Journal of Automation and Computing |
| 作者单位 | 1. 3. Faculty of Arts Computing Engineering and Sciences, Sheffield Hallam University, Sheffield S1 1WB, UK 2.School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK 3.School of Computer Science and Technology, Xi′an University of Posts and Telecommunications, Xi′an 710121, China |
| 推荐引用方式 GB/T 7714 | Yu Hao,Zhi-Jie Xu,Ying Liu,et al. Effective Crowd Anomaly Detection Through Spatio-temporal Texture Analysis[J]. International Journal of Automation and Computing,2019,16(1):27-39. |
| APA | Yu Hao,Zhi-Jie Xu,Ying Liu,Jing Wang,&Jiu-Lun Fan.(2019).Effective Crowd Anomaly Detection Through Spatio-temporal Texture Analysis.International Journal of Automation and Computing,16(1),27-39. |
| MLA | Yu Hao,et al."Effective Crowd Anomaly Detection Through Spatio-temporal Texture Analysis".International Journal of Automation and Computing 16.1(2019):27-39. |
入库方式： OAI收割
来源：自动化研究所
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