Unsupervised Video Surveillance for Anomaly Detection of Street Traffic
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 12
Abstract
Intelligent transportation systems enables the analysis of large multidimensional street traffic data to detect pattern and anomaly, which otherwise is a difficult task. Advancement in computer vision makes great contribution in the progress of video based traffic surveillance system. But still there are some challenges which need to be solved like objects occlusion, behavior of objects. This paper developed a novel framework which explores multidimensional data of road traffic to analyze different patterns of traffic and anomaly detection. This framework is implemented on road traffic dataset collected from different areas of the city.
Authors and Affiliations
Muhammad Umer Farooq, Najeed Ahmed Khan, Mir Shabbar Ali
Keywords
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- EP ID EP258406
- DOI 10.14569/IJACSA.2017.081234
- Views 97
- Downloads 0
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