Analysis and recognition of walking movements

Author

Davis, James W. ; Taylor, Stephanie R.

Author_Institution

Dept. of Comput. & Inf. Sci., Ohio State Univ., Columbus, OH, USA

Volume

1

fYear

2002

fDate

2002

Firstpage

315

Abstract

We present an approach for recognizing human walking movements using low-level motion regularities and constraints. Biomechanical features for classification are automatically extracted from video sequences of walkers. A multiplicative classification rule using statistical distances is then used to determine whether an unknown motion is consistent with normal walking patterns. Recognition results are shown distinguishing walking examples across multiple speeds from other nonwalking locomotions.

Keywords

image classification; image motion analysis; image sequences; sequences; statistical analysis; video signal processing; biomechanical feature classification; feature extraction; human walking movement analysis; human walking movement recognition; low-level motion constraints; low-level motion regularities; multiplicative classification rule; nonwalking locomotions; normal walking patterns; statistical distances; unknown motion; video sequences; Computerized monitoring; Data mining; Hidden Markov models; Humans; Information science; Legged locomotion; Subspace constraints; Surveillance; Tracking; Video sequences;

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.2002.1044702

Filename

1044702