Video ingress system for surveillance video querying
Name
1193030483-MIT.pdf
Size
404.4 KB
Format
Adobe PDF
Checksum (MD5)
72fb00a8df06d44f285fbb28fc31c677
Author(s)
Sipser, Aaron(Aaron J.)
Advisor(s)
Michael R. Stonebraker.
Date Issued
2020
Publisher
Massachusetts Institute of Technology
Abstract
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.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 39-41).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
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