Name
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. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ICIP.2005.1530385 | 2005 International Conference on Image Processing (ICIP), Vols 1-5 |
Keywords | Field | DocType |
component, pedestrian detection, motion analysis, spline interpolation, PCA, SVM | Object detection,Computer vision,Pattern recognition,Computer science,Support vector machine,Feature extraction,Artificial intelligence,Invariant (mathematics),Biometrics,Motion analysis,Pedestrian detection,Principal component analysis | Conference |
ISSN | Citations | PageRank |
1522-4880 | 9 | 0.74 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laszlo Havasi | 1 | 66 | 6.80 |
| Zoltán Szlávik | 2 | 116 | 21.40 |
| Tamás Szirányi | 3 | 152 | 26.92 |