Abstract
Human activity recognition is a critical territory of video data analysis and applications. The objective of activity recognition is to examine data patterns in the sequence of images of a particular human action video. Several applications of human action recognition includes surveillance systems, medical diagnostics, sports video data analysis, communication amongst people and electronic gadgets. In this paper we have reviewed various methodologies of human action recognition proposed by various researchers in the recent years. The methodologies are based on different behavioral patterns and feature extraction elements. A careful examination of the openly available standard datasets for activity recognition is done. Various classifiers were analyzed for effective human action recognition based on the feature extraction datasets. The paper concludes with open ending research issues related to human action recognition.
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