Eigenwalks: walk detection and biometrics from symmetry patterns

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Eigenwalks: walk detection and biometrics from symmetry patterns
In this paper we present a symmetry-based approach which can be used to detect humans and to extract biometric characteristics from video image-sequences. The method employs a simplified symmetry-feature extracted from the images. To obtain a useful descriptor of a walking person, we track temporally the symmetries which result from the movements of the person's legs. In a further processing stage these patterns are filtered, then re-sampled using Bezier-splines to generate an invariant and noise-cleaned signature or "feature". In our detection method the extracted spatio-temporal feature with a large number of dimensions (800) is transformed to a space with a much smaller number of dimensions (3), which we call the "eigenwalks space"; the method uses Principal Component Analysis (PCA) to reduce the dimensionality, and the Support Vector Machine (SVM) method in the eigenspace for recognition purposes. Finally we present a method by which we can estimate the gai...
Laszlo Havasi, Tamás Szirányi, Zolt&
Added 23 Oct 2009
Updated 14 Nov 2009
Type Conference
Year 2005
Where ICIP
Authors Laszlo Havasi, Tamás Szirányi, Zoltán Szlávik
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