An Efficient Gait Recognition System For Human Identification
Biometric systems are becoming increasingly important, as they provide more reliable and ef icient means of identity verification. Human identification at a distance has recently gained enormous interest among computer vision researchers. Gait recognition aims essentially to address this problem by recognising people based on the way they walk. In this paper, we propose an ef icient self-similarity based gait recognition system for human identification using modified Independent Component Analysis (MICA). Initially the background modelling is done from a video sequence. Subsequently, the moving foreground objects in the individual image frames are segmented using the background subtraction algorithm. Then, the morphological skeleton operator is used to track the moving silhouettes of a walking figure. The MICA based on eigenspace transformation is then trained using the sequence of silhouette images. Finally, when a video sequence is fed, the proposed system recognizes the gait features and thereby humans, based on self-similarity measure. The proposed system is evaluated using gait databases and the experimentation on outdoor video sequences demonstrates that the proposed algorithm achieves a pleasing recognition performance.
Biometric systems for human identification at distance have ever been an increasing demand in various significant applications. Many biometric resources, for instance iris, fingerprint, palmprint, hand geometry have been systematically studied and employed in many systems. In spite of their widespread applications, these resources suffer from two main disadvantages: 1) Failure to match in low resolution images, pictures taken at a distance and 2) Necessitates user cooperation for accurate results . For these reasons, innovative biometric recognition methods for human identification at a distance have been an urgent need for surveillance applications and gained immense attention among the computer vision community researchers in recent years. In this modern era, the integration of human motion analysis and biometrics has fascinated several security-sensitive environments such as military, banks, parks and airports etc and has turned out to be a popular research direction. Human gait recognition works from the observation that an individual’s walking style is unique and can be used for human identification. So as to recognize individual’s walking characteristics, gait recognition includes visual cue extraction as well as classification. But the major issue here is the representation of the gait features in an efficient manner
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