Gait recognition is a multistage process. It is important that gait capturing is performed in environments where the background is as uniform as possible. Moreover, since gait recognition algorithms are not, in general, invariant to the capturing viewpoint, care must be taken to conduct capturing from an appropriate viewpoint. Preferably, the walking subject should be walking in a direction perpendicular to the optical axis of the capturing device since the side view of walking individuals discloses the most information about their gait.
Once a walking sequence is captured, the walking subject is separated from its background using a process called background subtraction. A critical step in gait recognition is feature extraction, i.e., the extraction, from video sequences depicting walking persons, of signals that can be used for recognition. This step is very important since there are numerous conceivable ways to extract signals from a gait video sequence, e.g., spatial, temporal, spatiotemporal, and frequency-domain feature extraction.Therefore, one must ensure that the feature extraction process compacts as much discriminatory information as possible. Finally, there is a recognition step, which aims to compare the extracted gait signals with gait signals that are stored in a database. Apart from the apparent usefulness of gait analysis in biometric applications, gait has several important non biometric applications that are summarized in the “Non biometric Applications of Gait”. DOWNLOAD
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