Matching shape sequences in video with applications in human movement analysis
We present an approach for comparing two sequences of deforming shapes using both parametric models and nonparametric methods. In our approach, Kendall's definition of shape is used for feature extraction. Since the shape feature rests on a non-Euclidean manifold, we propose parametric models l...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 27(2005), 12 vom: 19. Dez., Seite 1896-909 |
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| Weitere Verfasser: | , |
| Format: | Aufsatz |
| Sprache: | English |
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2005
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Comparative Study Journal Article Research Support, U.S. Gov't, Non-P.H.S. |
| Zusammenfassung: | We present an approach for comparing two sequences of deforming shapes using both parametric models and nonparametric methods. In our approach, Kendall's definition of shape is used for feature extraction. Since the shape feature rests on a non-Euclidean manifold, we propose parametric models like the autoregressive model and autoregressive moving average model on the tangent space and demonstrate the ability of these models to capture the nature of shape deformations using experiments on gait-based human recognition. The nonparametric model is based on Dynamic Time-Warping. We suggest a modification of the Dynamic time-warping algorithm to include the nature of the non-Euclidean space in which the shape deformations take place. We also show the efficacy of this algorithm by its application to gait-based human recognition. We exploit the shape deformations of a person's silhouette as a discriminating feature and provide recognition results using the nonparametric model. Our analysis leads to some interesting observations on the role of shape and kinematics in automated gait-based person authentication |
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| Beschreibung: | Date Completed 19.01.2006 Date Revised 15.11.2006 published: Print Citation Status MEDLINE |
| ISSN: | 1939-3539 |