University of Twente Student Theses
Computer Vision for Crime Recognition Based on Skeleton Trajectories
Averchenko, Illya (2023) Computer Vision for Crime Recognition Based on Skeleton Trajectories.
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| Abstract: | Given the substantial amount of data generated daily by surveillance systems in urban areas, there is a growing necessity for automation in the crime detection process. Considering the limitations of the current approaches to detecting crime in surveillance videos, there is a need for a new approach that helps reduce human labor and its decision-making ability to ensure the safety of the public. The objective of this research to evaluate the accuracy of skeleton-based action recognition models within the crime domain and use the HR-Crime dataset as the reference point for comparison with other modalities. |
| Item Type: | Essay (Bachelor) |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 54 computer science |
| Programme: | Computer Science BSc (56964) |
| Link to this item: | https://purl.utwente.nl/essays/96126 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
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