Title :
Video events recognition by scene and group context
Author :
Pei Mingtao ; Wang Yafei ; Zhao Meng
Author_Institution :
Sch. of Comput. Sci., Beijing Inst. of Technol., Beijing, China
Abstract :
The ability to recognise video events has become increasingly more popular owing to its extensive practical applications. Most events will occur in certain scene with certain people, and the scene context and group context provide important information for event recognition. In this paper, we present an algorithm to recognise video events in different scenes in which there are multiple agents. First, we recognise events for each agent based on Stochastic Context Sensitive Grammar (SCSG). Then we propose the model of a scene in order to infer the scene in which the events occur, and we use a co-occurrence matrix of events to represent the group context. Finally, the scene and group context are exploited to distinguish events having similar structures. Experimental results show that by adding the scene and group context, the performance of events recognition can be significantly improved.
Keywords :
context-sensitive grammars; image recognition; stochastic processes; SCSG; cooccurrence event matrix; group context; multiple agent; scene context; stochastic context sensitive grammar; video event recognition; Atomic clocks; Context awareness; Grammar; Histograms; Stochastic processes; Training data; events recognition; group context; scene context;
Journal_Title :
Communications, China
DOI :
10.1109/CC.2013.6674220