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Conference Paper Abnormal Detection based on User Feedback for Abstracted Pedestrian Video
Cited 6 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Ho-chul Shin
Issue Date
2019-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2019, pp.1036-1038
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC46691.2019.8939600
Abstract
in this study, we present the abstracted pedestrian behavior representation and abnormal detection method based on user feedback for pedestrian video surveillance system. Video surveillance data is large in size and difficult to process in real time. To solve this problem, we suggested a method of expressing the pedestrian behavior with abbreviated map. In the video surveillance system, false detection of an abnormal situation becomes a big problem. If surveillance user can guide the false detection case as human in the loop, the surveillance system can learn the case and reduce the false detection error in the future. We suggested user feedback based abnormal pedestrian detection method. By the suggested user feedback algorithm, the false detection can be reduced to less than 0.5%.
KSP Keywords
Abnormal situation, Behavior representation, Detection Method, False detection, Real-time, User feedback, Video surveillance system, abnormal detection, detection error, human-in-The-loop, pedestrian behavior