Human activity analysis is receiving increasing attention from computer vision researchers. This interest is motivated by a wide spectrum of applications

such as surveillance

man-machine interfaces

video coding

and so on. It has been a hot research in image analysis

psychology

and neurophysiology. This paper gives an overview of the various tasks involved in image analysis field. We focus on three major areas:（1) development history of the activity analysis

（2) important and novel ideas

（3) open problems for future research. Research about activity analysis was originated 30 years ago. In the recent years

increasing attention has been paid to this field. The two basic problems of activity analysis are the representation and the recognition of activity. This paper reviews the existing algorithms based on the two basic problems. The representation of the activity can be classified into two classes: the methods based on low-level image information and the methods based on the high level human model. And there are two kinds of activity recognition algorithms: template matching methods and state space methods. Finally

some research challenges and future directions are discussed.