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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Havasi, L. Szlavik, Z. Sziranyi, T. |
| Copyright Year | 2005 |
| Description | Author affiliation: Fac. of Inf. Technol., Peter Pazmany Catholic Univ., Budapest, Hungary (Havasi, L.) |
| Abstract | 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 gait-parameters (the beginning and end of a walk-cycle, identification of the leading leg) from the symmetry-patterns of the walking person, without camera calibration, based on two successive detected walk-steps. |
| File Size | 266723 |
| File Format | |
| ISBN | 0780391349 |
| DOI | 10.1109/ICIP.2005.1530385 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-09-14 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Biometrics Legged locomotion Leg Principal component analysis Support vector machines Humans Tracking Noise generators Feature extraction Cameras SVM component pedestrian detection motion analysis spline interpolation PCA |
| Content Type | Text |
| Resource Type | Article |
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