Human Action Classification and Unusual Action Recognition Algorithm for Intelligent Surveillance System
This paper suggests an algorithm to classify human actions for the intelligent surveillance system. In order to classify actions, the proposed method calculates the difference image between input images and modeled background, uses motion information histogram and traces of center points of objects. Human actions are categorized into four types: they are the most frequently three actions people take walking, sitting, standing up and unusual action like as sudden falling down. We examine the proposed method on eight people with a sequence captured by using a web camera and the result shows that the proposed method classifies human actions well and recognitions of the unusual action.
KeywordsSilhouette Object tracking Auto detection Surveillance
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012-0002852).
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