Human re-identification in real-world surveillance camera networks

Authors
Li, Yang
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Other Contributors
Radke, Richard J., 1974-
Stewart, Charles V.
Ji, Qiang, 1963-
Saulnier, Gary J.
Issue Date
2015-05
Keywords
Electrical engineering
Degree
PhD
Terms of Use
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
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Abstract
Video surveillance has become critical for security applications. With cameras and data storage devices getting more affordable, many institutions and organizations have chosen to install camera networks for safety and surveillance. The U.S. Department of Homeland Security, for instance, has directed a huge amount of manpower and expenditure to the installation, maintenance, replacement and operation of surveillance camera networks. Public transportation centers such as airports, train stations, and bus stops are some of the most concentrated environments. The traditional monitoring method, which completely relies on security officers' observations, becomes less feasible when more and more screens need to be watched at the same time. Instead, video analytic solutions that process multiple cameras simultaneously are more reliable. In this thesis, we focus on one particular application, human re-identification, with a focus on the challenges of real-world scenarios.
Description
May 2015
School of Engineering
Department
Dept. of Electrical, Computer, and Systems Engineering
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
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