Gait Recognition System

Gait refers to the manner in which a person walks, and is one of the few biometric traits that can be used to recognize people at a distance. Therefore, this trait is very appropriate in surveillance scenarios. Most gait recognition algorithms attempt to extract the human silhouette in order to derive the gait variables. Hence, the selection of a good model to represent the human body is pivotal to the efficient functioning of a gait recognition system. However, the gait of an individual is affected by footwear, clothing, affliction of the legs, or walking surface.

Walking is a complex dynamic activity that is fast, animate, irreversible and also rigid. Many components of the body are involved in moving and interact mutually with each other

From a surveillance perspective, walk pattern biometrics is appealing because of its possibility to be performed at a distance, even surreptitiously. Together with high rate of collectability these are the reasons why the method is preferably employed at human identification rather than authentication.

Unlike face recognition, which can be easily affected by low resolution, here a video of reduced quality has been often sufficient. Moreover, gait is difficult to disguise, and by trying to do so the individual will probably appear even more suspicious, while face can easily be altered or hidden.

On the other hand, slightly modified conditions may introduce a large appearance change, which may lead to a failure in recognition. Gait can be affected by clothing (long cloak, shoes, and carrying objects), physical changes (pregnancy, injury, weight gain/loss) or environmental context (walking surface, background). Temporary stimulants (drugs and alcohol) as well as mood can change a person’s walking

Moreover, it also detects and reports any anomaly in a human gait in real time mode. The challenges involved in gait recognition include also imperfect foreground segmentation of the walking subject from the background scene and variations in the camera viewing angle with respect to the walking subjects.

1.6 Gait Detection

Detection and tracking humans from a video sequence is the first step in gait recognition, where an individual is actually spotted walking. Gait detection systems usually work with the assumption that the video sequence to be processed is captured by a static camera, and the only moving object in video sequence is the subject (person). Given a video sequence from a static camera, this module detects and tracks the moving silhouettes.

1.7 Gait Recognition

Recently extracted samples are compared to the entries stored in a central database. The identity of an individual holding the most (and enough) similar gait sample is picked and stated as the recognition verdict. Gait recognition system can be used in a number of different scenarios. If an individual walks by the camera who’s gait has been previously recorded and he is a known threat, then the system will recognize him and the appropriate authorities can be automatically alerted. Such systems have a large amount of potential application in airports, banks or other high security