DocumentCode :
384445
Title :
Temporal PDMs for gait classification
Author :
Tassone, Ezra ; West, Geoff ; Venkatesh, Svetha
Author_Institution :
Sch. of Comput. Sci., Curtin Univ. of Technol., Perth, WA, Australia
Volume :
2
fYear :
2002
fDate :
2002
Firstpage :
1065
Abstract :
Gait classification is a developing research area, particularly with regards to biometrics. It aims to use the distinctive spatial and temporal characteristics of human motion to classify differing activities. As a biometric, this extends to recognising different people by the heterogeneous aspects of their gait. This research aims to use a modified deformable model, the temporal PDM, to distinguish the movements of a walking and running person. The movement of 2D points on the moving form is used to provide input into the model and classify the type of gait present.
Keywords :
biometrics (access control); gait analysis; image motion analysis; 2D point movement; biometrics; gait classification; human motion; modified deformable model; person recognition; running person; spatial characteristics; temporal PDM; temporal characteristics; walking person; Australia; Biometrics; Covariance matrix; Deformable models; Eigenvalues and eigenfunctions; Humans; Image recognition; Legged locomotion; Optical films; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-1695-X
Type :
conf
DOI :
10.1109/ICPR.2002.1048489
Filename :
1048489
Link To Document :
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