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摘要
Action recognition has become an active area of research in the field of video surveillance. In this paper, a local space-time constraint Markov random fields (MRFs) model is proposed for the recognition of multi-view action based on the posture's articulation points from the sensor networks in the smart family space. The position distribution under different views and the time continuity of the posture sequence are used as the random field to label the corresponding action classes. Experimental results show that the proposed model can accurately recognise the actions of objects under multi-views in the family environment and requires low running time.
- 出版日期2017
- 单位燕山大学
