RETRACTED: Design of intelligent community security system based on visual tracking and large data natural language processing technology (Retracted Article)

被引:6
作者
Daming, Li [1 ,2 ]
Lianbing, Deng [3 ,4 ]
Zhiming, Cai [5 ]
Kaicheng, Cai [6 ]
机构
[1] Zhuhai Da Hengqin Sci & Technol Dev Co Ltd, Postdoctoral Res Ctr, Hengqin, Peoples R China
[2] City Univ Macau, Taipa, Macao, Peoples R China
[3] Huazhong Univ Sci & Technol, Wuhan, Hubei, Peoples R China
[4] Zhuhai Da Hengqin Sci & Technol Dev Co Ltd, Hengqin, Peoples R China
[5] City Univ Macao, Inst Data Sci, Taipa, Macao, Peoples R China
[6] Guangzhou Automobile Grp Co Ltd, Automot Engn Res Inst, Guangzhou, Guangdong, Peoples R China
基金
中国博士后科学基金; 国家重点研发计划;
关键词
Video surveillance system; big data; community security; early warning system; EXPERT-SYSTEM; SMART; REVIEWS; SET;
D O I
10.3233/JIFS-179789
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the improvement of public security awareness, it is of great value to establish an intelligent crowd screening video early warning system for community security. The method is to use artificial intelligence and big data technology to analyze the facial features of past people through video data in video surveillance. In this paper, the authors analyze the design of intelligent community security system based on visual tracking and large data natural language processing technology. Through JMF technology and video acquisition card, the signal can be transmitted from the matrix machine to the server of the system. In the process of transmission, we also need to use multi-threading technology and double buffer technology to compress video, which can improve the compression efficiency and reduce the CPU usage time. The information module is mainly responsible for receiving and playing video. This module needs JAVA technology which can receive video. Once the client requests monitoring, the client can immediately send relevant operation instructions to the server, and the server will return the corresponding video stream in time. The simulation results show that the system can identify risks efficiently and accurately.
引用
收藏
页码:7107 / 7117
页数:11
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