Abstract
The significance of Real Time video surveillance System has been raised up due to increased importance in safety and security. The Proposed Real Time video surveillance system is capable of detecting, classifying and tracking objects of interest (human). This can be done by using Gait Analysis for tracking scenarios and generating notification to authoritative person. Gait Analysis helps us to identify people by their walking style. Because of this exquisite feature we used gait recognition in proposed real time video surveillance system. In this proposed system for depicting human walking properties for individual recognition i.e. for performing feature extraction we have used a new spatio-temporal gait representation called as Gait Energy Image (GEI). GEI represents a human motion sequence in a single image while preserving temporal information. For human recognition we have used Statistical GEI feature matching, wherein to reduce dimensionality problem of GEI's, we used two approaches they are Principal Component Analysis (PCA) and its variants Multiple Discriminant Analysis (MDA).
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