Name
Abstract | ||
|---|---|---|
This paper focuses on the use of Hidden Markov Models (HMMs) for structure analysis of sport videos. The video structure parsing relies on the analysis of the temporal inter- leaving of video shots, with respect to a priori information about video content and editing rules. The basic temporal unit is the video shot and visual features are used to char- acterize its type of view. Our approach is validated in the particular domain of tennis videos. As a result, typical ten- nis scenes are identified. In addition, each shot is assigned to a level in the hierarchy described in terms of point, game and set. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/ICIP.2003.1246859 | Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference |
Keywords | Field | DocType |
hidden Markov models,image retrieval,video signal processing,HMM,hidden markov models,hierarchical structure analysis,image retreival,sport videos,temporal interleaving | Structure analysis,Computer vision,Pattern recognition,Computer science,A priori and a posteriori,Image retrieval,Artificial intelligence,Parsing,Hierarchy,Hidden Markov model,Interleaving | Conference |
Volume | ISSN | ISBN |
2 | 1522-4880 | 0-7803-7750-8 |
Citations | PageRank | References |
23 | 1.10 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kijak, E. | 1 | 23 | 1.10 |
| Lionel Oisel | 2 | 23 | 1.10 |
| Patrick Gros | 3 | 23 | 1.10 |