Surveillance technology is now ubiquitous in modern society.  This is due to  the increasing number of crimes as well as the vital need to provide a safer environment. Because of the rapid growth  of security cameras and incapability of manpower to supervise them, the deployment of biometric technologies becomes important for the development of automated visual surveillance systems. Recently, the use of gait for people identification in surveillance applications has attracted researchers from  computer vision.  The suitability of gait recognition for surveillance systems emerges from the fact that gait can be perceived from a distance as well as its non-invasive nature. Although gait recognition is still a new biometric and is not sufficiently mature to be deployed in real world applications such as visual surveillance, it overcomes most of the limitations that other biometrics suffer from such as face, fingerprints and iris recognition which can be obscured in most situations where serious crimes are involved.

Although people can discern the state of the subject from a single static image, motion pictures provide even more rich and reliable information for the perception of the different biological, social and psychological characteristics of the person such as emotions, actions and personality traits of the subject. This is because the acquired perceptual knowledge is encoded in the human motion. Furthermore, this notion was also observed by Darwin (1872) in his book “The Expression of Emotions in Man and Animals” where it was stated:

Actions speak louder than pictures when it comes to understanding what others are doing.

The human visual system is very sensitive to motion as it tends to focus attention on moving objects. In contrast to static or motionless objects, which are not as straightforward to detect. Motion is a spatio-temporal event defined as the change of spatial location over time. Given some visual input, the perception of motion is regarded as the process by which the visual system acquires perceptual knowledge about the speed and direction of the moving object. Whilst this process is spontaneous for the human visual system, it has proven to be extraordinarily difficult to duplicate this capability into computer vision systems.