Motion-Based Recognition of People in EigenGait Space

A motion-based, correspondence-free technique for human gait recognition in monocular video is presented. We contend that the planar dynamics of a walking person are encoded in a 2D plot consisting of the pairwise image similarities of the sequence of images of the person, and that gait recognition can be achieved via standard pattern classification of these plots. We use background modelling to track the person for a number of frames and extract a sequence of segmented images of the person. The self-similarity plot is computed via correlation of each pair of images in this sequence. For recognition, the method applies Principal Component Analysis to reduce the dimensionality of the plots, then uses the k-nearest neighbor rule in this reduced space to classify an unknown person. This method is robust to tracking and segmentation errors, and to variation in clothing and background. It is also invariant to small changes in camera viewpoint and walking speed. The method is tested on out...

• Type: Conference
• Year: 2002
• Where: FGR
• Authors: Chiraz BenAbdelkader, Larry S. Davis, Ross Cutler
• Keywords: Biometrics, FGR 2002, Gait Recognition, Human Gait Recognition, Images