| dc.contributor.advisor | Michael R. Stonebraker. | en_US |
| dc.contributor.author | Sipser, Aaron(Aaron J.) | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2020-09-15T22:02:09Z | |
| dc.date.available | 2020-09-15T22:02:09Z | |
| dc.date.copyright | 2020 | en_US |
| dc.date.issued | 2020 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1721.1/127525 | |
| dc.description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020 | en_US |
| dc.description | Cataloged from the official PDF of thesis. | en_US |
| dc.description | Includes bibliographical references (pages 39-41). | en_US |
| dc.description.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. | en_US |
| dc.description.statementofresponsibility | by Aaron Sipser. | en_US |
| dc.format.extent | 41 pages | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | 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. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Electrical Engineering and Computer Science. | en_US |
| dc.title | Video ingress system for surveillance video querying | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | M. Eng. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.identifier.oclc | 1193030483 | en_US |
| dc.description.collection | M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science | en_US |
| dspace.imported | 2020-09-15T22:02:08Z | en_US |
| mit.thesis.degree | Master | en_US |
| mit.thesis.department | EECS | en_US |
