Anomaly detection and prediction of human actions in a video surveillance environment
| dc.contributor.advisor | Potgieter, Anet | en_ZA |
| dc.contributor.author | Spasic, Nemanja | en_ZA |
| dc.date.accessioned | 2014-08-13T19:27:28Z | |
| dc.date.available | 2014-08-13T19:27:28Z | |
| dc.date.issued | 2007 | en_ZA |
| dc.description | Includes bibliographical references (leaves 129-135). | en_ZA |
| dc.description.abstract | World wide focus has over the years been shifting towards security issues, not in least due to recent world wide terrorist activities. Several researchers have proposed state of the art surveillance systems to help with some of the security issues with varying success. Recent studies have suggested that the ability of these surveillance systems to learn common environment behaviour patterns as well as to detect and predict unusual, or anomalous, activities based on those learnt patterns are possible improvements to those systems. I addition, some of these surveillance systems are still run by human operators, who are prone to mistakes and may need some help from the surveillance systems themselves in detection of anomalous activities. This dissertation attempts to address these suggestions by combining the fields of image understanding and artificial intelligence, specifically Bayesian Networks, to develop a prototype video surveillance system that can learn common environmental behaviour patterns, thus being able to detect and predict anomalous activity in the environment based on those learnt patterns. In addition, this dissertatio aims to show how the prototpe system can adapt to these anomalous behaviours and integrate them into its common patterns over a prolonged occurrence period. | en_ZA |
| dc.identifier.apacitation | Spasic, N. (2007). <i>Anomaly detection and prediction of human actions in a video surveillance environment</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Computer Science. Retrieved from http://hdl.handle.net/11427/6377 | en_ZA |
| dc.identifier.chicagocitation | Spasic, Nemanja. <i>"Anomaly detection and prediction of human actions in a video surveillance environment."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Computer Science, 2007. http://hdl.handle.net/11427/6377 | en_ZA |
| dc.identifier.citation | Spasic, N. 2007. Anomaly detection and prediction of human actions in a video surveillance environment. University of Cape Town. | en_ZA |
| dc.identifier.ris | TY - Thesis / Dissertation AU - Spasic, Nemanja AB - World wide focus has over the years been shifting towards security issues, not in least due to recent world wide terrorist activities. Several researchers have proposed state of the art surveillance systems to help with some of the security issues with varying success. Recent studies have suggested that the ability of these surveillance systems to learn common environment behaviour patterns as well as to detect and predict unusual, or anomalous, activities based on those learnt patterns are possible improvements to those systems. I addition, some of these surveillance systems are still run by human operators, who are prone to mistakes and may need some help from the surveillance systems themselves in detection of anomalous activities. This dissertation attempts to address these suggestions by combining the fields of image understanding and artificial intelligence, specifically Bayesian Networks, to develop a prototype video surveillance system that can learn common environmental behaviour patterns, thus being able to detect and predict anomalous activity in the environment based on those learnt patterns. In addition, this dissertatio aims to show how the prototpe system can adapt to these anomalous behaviours and integrate them into its common patterns over a prolonged occurrence period. DA - 2007 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2007 T1 - Anomaly detection and prediction of human actions in a video surveillance environment TI - Anomaly detection and prediction of human actions in a video surveillance environment UR - http://hdl.handle.net/11427/6377 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/6377 | |
| dc.identifier.vancouvercitation | Spasic N. Anomaly detection and prediction of human actions in a video surveillance environment. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Computer Science, 2007 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/6377 | en_ZA |
| dc.language.iso | eng | en_ZA |
| dc.publisher.department | Department of Computer Science | en_ZA |
| dc.publisher.faculty | Faculty of Science | en_ZA |
| dc.publisher.institution | University of Cape Town | |
| dc.subject.other | Computer Science | en_ZA |
| dc.title | Anomaly detection and prediction of human actions in a video surveillance environment | en_ZA |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationname | MSc | en_ZA |
| uct.type.filetype | Text | |
| uct.type.filetype | Image | |
| uct.type.publication | Research | en_ZA |
| uct.type.resource | Thesis | en_ZA |
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