Automated recognition of sequential patterns in captured motion streams
Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Title of host publication | Web-Age Information Management |
| Subtitle of host publication | 11th International Conference, WAIM 2010, Proceedings |
| Publisher | Springer Verlag |
| Pages | 250-261 |
| Volume | 6184 LNCS |
| ISBN (Print) | 3642142451, 9783642142451 |
| Publication status | Published - 2010 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 6184 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Conference
| Title | 11th International Conference on Web-Age Information Management, WAIM 2010 |
|---|---|
| Place | China |
| City | Jiuzhaigou |
| Period | 15 - 17 July 2010 |
Link(s)
Abstract
Motion capture data has been frequently used in computer animation and video games. Motions are often captured in a continuous manner such that a motion contains multiple patterns joined sequentially without obvious breakpoints between them. It is challenging to learn the captured motions as it requires both segmentation and recognition. In this paper, a new method based on an extension of open-end dynamic time warping (OE-DTW) is proposed to automatically segment and recognize sequential patterns in motion streams. To enhance the performance, we introduce a global constraint of K-Repetition on OE-DTW and a flexible end point detection scheme. In the experiments, we applied our method on different classes of dance motions and demonstrated the effectiveness of our method by comparing with existing approach. © 2010 Springer-Verlag.
Research Area(s)
- continuous dynamic programming, Dance motion, global constraint, open-end DTW, segmentation and recognition, sequential pattern
Citation Format(s)
Automated recognition of sequential patterns in captured motion streams. / Deng, Liqun; Leung, Howard; Gu, Naijie; Yang, Yang.
Web-Age Information Management: 11th International Conference, WAIM 2010, Proceedings. Vol. 6184 LNCS Springer Verlag, 2010. p. 250-261 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6184 LNCS).Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
