In the past few years, violence detection has become an increasingly rele-
vant topic in computer vision with many proposed solutions by researchers. This
thesis proposes a solution called Criminal Aggression Recognition Engine (CARE),
an OpenCV based Java implementation of a violence detection system that can be
trained with video datasets to classify action in a live feed as non-violent or violent.
The algorithm extends existing work on fast ght detection by implementing violence
detection of live video, in addition to prerecorded video. The results for violence
detection in prerecorded videos are comparable to other popular detection systems
and the results for live video are also very encouraging, making the work proposed in
this thesis a solid foundation for improved live violence detection systems. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection
| Identifer | oai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_33912 |
| Contributors | Eneim, Maryam (author), Marques, Oge (Thesis advisor), Florida Atlantic University (Degree grantor), College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science |
| Publisher | Florida Atlantic University |
| Source Sets | Florida Atlantic University |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation, Text |
| Format | 55 p., application/pdf |
| Rights | Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder., http://rightsstatements.org/vocab/InC/1.0/ |
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