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.
| Original language | English |
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| Title of host publication | 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings |
| Pages | V537-V540 |
| Publication status | Published - 2006 |
| Externally published | Yes |
| Event | 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France Duration: 14 May 2006 → 19 May 2006 |
Publication series
| Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
|---|---|
| Volume | 5 |
| ISSN (Print) | 1520-6149 |
Conference
| Conference | 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 |
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| Country/Territory | France |
| City | Toulouse |
| Period | 14/05/06 → 19/05/06 |
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Li, C., Kulkarni, P. R., & Prabhakaran, B. (2006). Motion stream segmentation and recognition by classification. In 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings (pp. V537-V540). Article 1661331 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 5).