Motion Stream Segmentation and Recognition by Classification

Author

Li, Chuanjun ; Kulkarni, Punit R. ; Prabhakaran, B.

Author_Institution

Dept. of Comput. Sci., Texas Univ., Dallas, TX

Volume

fYear

2006

fDate

14-19 May 2006

Abstract

This paper proposes a classification-based approach to segmenting and recognizing patterns in motion signals. Feature vectors are extracted based on singular value decomposition (SVD) for classification. Multi-class support vector machine (SVM) classifiers with class probability estimates are explored for segmenting and recognizing motion streams. Experiments show that the proposed approach can find patterns in the multi-attribute motion streams with high accuracy

Keywords

image classification; image motion analysis; image segmentation; probability; singular value decomposition; support vector machines; SVD; SVM; classification-based approach; motion signals; motion stream segmentation; pattern recognition; singular value decomposition; support vector machine; Animation; Data gloves; Feature extraction; Matrix decomposition; Motion analysis; Pattern recognition; Singular value decomposition; Streaming media; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on

Conference_Location

Toulouse

ISSN

1520-6149

Print_ISBN

1-4244-0469-X

Type

conf

DOI

10.1109/ICASSP.2006.1661331

Filename

1661331

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2331734