NDLI: Video entity resolution: Applying ER techniques for Smart Video Surveillance

Content Provider	IEEE Xplore Digital Library
Author	Liyan Zhang Vaisenberg, R. Mehrotra, S. Kalashnikov, D.V.
Copyright Year	2011
Description	Author affiliation: Department of Computer Science, University of California, Irvine, USA (Liyan Zhang; Vaisenberg, R.; Mehrotra, S.; Kalashnikov, D.V.)
Abstract	Smart Video Surveillance (SVS) applications enhance situational awareness by allowing domain analysts to focus on the events of higher priority. This in turn leads to improved decision making, allows for better resource management, and helps to reduce information overload. SVS approaches operate by trying to extract and interpret higher “semantic” level events that occur in video. On of the key challenges of Smart Video Surveillance is that of person identification where the task is for each subject that occur in a video shot to identify the person it corresponds to. The problem of person identification is very complex in the resource constrained environments where transmission delay, bandwidth restriction, and packet loss may prevent the capture of high quality data. In this paper we connect the problem of person identification in video data with the problem of entity resolution that is common in textual data. Specifically, we show how the PI problem can be successfully resolved using a graph-based entity resolution framework called RelDC that leverages relationships among various entities for disambiguation. We apply the proposed solution to a dataset consisting of several weeks of surveillance videos. The results demonstrate the effectiveness and efficiency of our approach even with low quality video data.
Starting Page	26
Ending Page	31
File Size	571548
Page Count	6
File Format	PDF
ISBN	9781612849386
e-ISBN	9781612849379
e-ISBN	9781612849362
DOI	10.1109/PERCOMW.2011.5766881
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-03-21
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Histograms Image color analysis Face recognition Feature extraction Surveillance Face Legged locomotion Video Data Cleaning Smart Video Surveillance Video Entity Resolution Person Identification
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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