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Anomaly detection and prediction of human actions in a video surveillance environment
Includes bibliographical references (leaves 129-135).
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Computer Science
2014
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| _version_ | 1867613320292335616 |
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| access_status_str | Open Access |
| author | Spasic, Nemanja |
| author2 | Potgieter, Anet |
| author_browse | Potgieter, Anet Spasic, Nemanja |
| author_facet | Potgieter, Anet Spasic, Nemanja |
| author_sort | Spasic, Nemanja |
| collection | Thesis |
| description | Includes bibliographical references (leaves 129-135). |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/6377 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:14.045Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | Department of Computer Science |
| publisherStr | Department of Computer Science |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/6377 Anomaly detection and prediction of human actions in a video surveillance environment Spasic, Nemanja Potgieter, Anet Computer Science Includes bibliographical references (leaves 129-135). 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. 2014-08-13T19:27:28Z 2014-08-13T19:27:28Z 2007 Master Thesis Masters MSc http://hdl.handle.net/11427/6377 eng application/pdf Department of Computer Science Faculty of Science University of Cape Town |
| spellingShingle | Computer Science Spasic, Nemanja Anomaly detection and prediction of human actions in a video surveillance environment |
| thesis_degree_str | Master's |
| title | Anomaly detection and prediction of human actions in a video surveillance environment |
| title_full | Anomaly detection and prediction of human actions in a video surveillance environment |
| title_fullStr | Anomaly detection and prediction of human actions in a video surveillance environment |
| title_full_unstemmed | Anomaly detection and prediction of human actions in a video surveillance environment |
| title_short | Anomaly detection and prediction of human actions in a video surveillance environment |
| title_sort | anomaly detection and prediction of human actions in a video surveillance environment |
| topic | Computer Science |
| url | http://hdl.handle.net/11427/6377 |
| work_keys_str_mv | AT spasicnemanja anomalydetectionandpredictionofhumanactionsinavideosurveillanceenvironment |