Comparative analysis study of human activity recognition using various techniques

A number of efforts have been applied on human activity recognition such as face recognition and motion analysis. The major problems in recognition are: 1. Scale. 2. Shift. 3. Projection. Human Activities are identified by the pose of the body such as standing, sitting etc. and some of the activities are like the emotions, facial expressions etc. Generally, human activity recognition is achieved by two groups of instruments so far; one on the basis of wearable sensors and the other one on the basis of environment sensing instruments. Wearable sensors are used like accelerometers, gyroscopes, and microphones and environment sensing instruments we use video recorders, shock sensors etc. Since the installation of the environment sensing instruments is intrusive and quite expensive so Wearable sensors are preferred. The Human Activity is recognized by combining information of human pose, human location and elapsed time. The main objective of this research is to recognize and summarize various activities of the human body by the help of the various techniques like Machine Learning, Sensor Technology etc. It will be helpful in commercial use like the restaurants and food places full of the automated robots and many more. It is also helpful in Medical field like full automated nurse robots available for the patient care etc. it is also helpful in security purposes and many more.