Human Identification Using Gait and Face

One of the main goals of computer vision research is to develop methods to recognize objects and events. A subclass of these topics is the recognition of humans and their activities. Gait recognition is related to the broader problem of human motion modeling and has important implications in such areas as surveillance, medical diagnoses, the entertainment industry, and video communications. Human gait is a spatio-temporal phenomenon concerning the motion of an individual. When identification is attempted in natural settings for surveillance applications, biometrics such as fingerprint or iris processes are not applicable. A person’s gait is best reflected from a side view to the camera. Various approaches for performing face recognition based on video sequences have been proposed. While face recognition has been a subject for research in computer vision for many years, the use of gait for recognition is a more recent phenomenon.