International Journal of Engineering and Technology

Action recognition is an essential in the field of visual surveillance system to identify the motion objects. This paper presents the adaptive neural fuzzy inference system for detecting the various human movements from the motion video sequences. Human body posture prototypes are identified by self organizing map. It also recognizes the continuous human movements in the video sequences. Fuzzy inference system is proposed to identify the action classification. This method maps, a set of input data into a set of desired output and it matches the data from the training and testing phase. Bayesian framework is used to recognize the various kinds of activities and produce the recognition results. The proposed work is able to detect continuous instances of similar action performed by several people in various view points accurately than other existing methods in the recent literature.