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Conference Paper
Pedestrian Video Data Abstraction and Classification for Surveillance System
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- Authors
- Ho-chul Shin, Jae-yeong Lee
- Issue Date
- 2018-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.1476-1478
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- In this study, we have developed abstracted pedestrian behavior representation and classification method for pedestrian video surveillance system. An effective intelligent surveillance system can be constructed if the high-resolution surveillance image information is efficiently summarized. The motion of the pedestrian is represented by a multi-layer grid map using a detector and a tracker. A normal pattern and anomalous pattern database were constructed and classified using the CNN classifier. With the abstracted pedestrian data and CNN network, the abnormal situation can be detected up to recall 92.0%, precision 99.9%.
- KSP Keywords
- Abnormal situation, Behavior representation, Classification method, Grid Map, High resolution, Image information, Intelligent surveillance system, Normal Pattern, Pattern database, Video data, Video surveillance system