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Proceedings Paper

Clothing mark index system with image saliency in surveillance videos
Author(s): Lili Jia; Wenbin Liu; Wei Chen
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Paper Abstract

In order to strengthen the management and control of special crowd and increase the application effectiveness of video as a typical unstructured data, this paper focuses on how to effectively extract and utilize the rich content contained in it to transform into intelligence information and build an effective personnel-specific tracking system. The experimental results show that the combination of video motion region extraction and personnel image features can more accurately complete person detection, and the introduction of multi-feature fusion to extract special person regions, such as clothing logo identification and other areas, for specific person to carry out feature labeling to index, improve the accuracy of personnel tracking. From the perspective of police technology innovation, this paper introduces the method of personnel characteristics analysis, comparison, retrieval, data mining and intelligent early warning to improve the application level of valuable personnel characteristics data in video images, and establish a feature analysis system to achieve continuous tracking of targets.

Paper Details

Date Published: 31 January 2020
PDF: 5 pages
Proc. SPIE 11427, Second Target Recognition and Artificial Intelligence Summit Forum, 114273Q (31 January 2020);
Show Author Affiliations
Lili Jia, Shanghai Institute of Criminal Science and Technology (China)
Shanghai Key Lab. of Field Evidence (China)
Wenbin Liu, Shanghai Institute of Criminal Science and Technology (China)
Shanghai Key Lab. of Field Evidence (China)
Wei Chen, Shanghai Key Lab. of Field Evidence (China)


Published in SPIE Proceedings Vol. 11427:
Second Target Recognition and Artificial Intelligence Summit Forum
Tianran Wang; Tianyou Chai; Huitao Fan; Qifeng Yu, Editor(s)

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