Video ingress system for surveillance video querying
Author(s)Sipser, Aaron(Aaron J.)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Michael R. Stonebraker.
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Police departments struggle to review surveillance footage in an efficient manner. Finding a person matching certain characteristics requires manually scrolling through video feeds, potentially wasting hundreds of valuable man-hours solving crimes. SurvQ is a video query system which automates this process. Many existing systems are either too computationally intensive or only work on one type of camera. SurvQ, instead, focuses on a real time ingest system which supports arbitrary video sources (body cameras, dash cams, CCTV) at scale. It then uses a combination of cheap object detection, on-demand analysis, and priority ranking to efficiently analyze relevant video. We found this approach could scale to several hundred cameras in real time, suitable for the use-case of an entire police department in West Lafayette, IN.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020Cataloged from the official PDF of thesis.Includes bibliographical references (pages 39-41).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.