| dc.contributor.advisor | Michael Stonebraker. | en_US |
| dc.contributor.author | Collins, Zachary(Zachary L.) | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2020-09-15T21:55:30Z | |
| dc.date.available | 2020-09-15T21:55:30Z | |
| dc.date.copyright | 2020 | en_US |
| dc.date.issued | 2020 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1721.1/127391 | |
| 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 45-46). | en_US |
| dc.description.abstract | Surveillance video is abundant in urban areas and can often be vital to police when conducting investigations. Currently, the only means investigators have of finding a suspect in video is to watch it from beginning to end. This can be tedious and waste numerous man hours that could be expended elsewhere. Survq is a system that aids police detectives by automatically identifying key features of video using novel machine learning algorithms. These features are then used to filter video to those that match a suspect description. In this paper, we present the interface used for investigation and how it was designed with this use case and underlying system in mind. | en_US |
| dc.description.statementofresponsibility | by Zachary Collins. | en_US |
| dc.format.extent | 46 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 | Active database interface for video search | 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 | 1192543880 | en_US |
| dc.description.collection | M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science | en_US |
| dspace.imported | 2020-09-15T21:55:30Z | en_US |
| mit.thesis.degree | Master | en_US |
| mit.thesis.department | EECS | en_US |
