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Proceedings Paper

A web-based video annotation system for crowdsourcing surveillance videos
Author(s): Neeraj J. Gadgil; Khalid Tahboub; David Kirsh; Edward J. Delp
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Paper Abstract

Video surveillance systems are of a great value to prevent threats and identify/investigate criminal activities. Manual analysis of a huge amount of video data from several cameras over a long period of time often becomes impracticable. The use of automatic detection methods can be challenging when the video contains many objects with complex motion and occlusions. Crowdsourcing has been proposed as an effective method for utilizing human intelligence to perform several tasks. Our system provides a platform for the annotation of surveillance video in an organized and controlled way. One can monitor a surveillance system using a set of tools such as training modules, roles and labels, task management. This system can be used in a real-time streaming mode to detect any potential threats or as an investigative tool to analyze past events. Annotators can annotate video contents assigned to them for suspicious activity or criminal acts. First responders are then able to view the collective annotations and receive email alerts about a newly reported incident. They can also keep track of the annotators’ training performance, manage their activities and reward their success. By providing this system, the process of video analysis is made more efficient.

Paper Details

Date Published: 3 March 2014
PDF: 12 pages
Proc. SPIE 9027, Imaging and Multimedia Analytics in a Web and Mobile World 2014, 90270A (3 March 2014); doi: 10.1117/12.2042440
Show Author Affiliations
Neeraj J. Gadgil, Purdue Univ. (United States)
Khalid Tahboub, Purdue Univ. (United States)
David Kirsh, Univ. of California, San Diego (United States)
Edward J. Delp, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 9027:
Imaging and Multimedia Analytics in a Web and Mobile World 2014
Qian Lin; Jan Philip Allebach; Zhigang Fan, Editor(s)

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