Name
Abstract | ||
|---|---|---|
The creation of a cognitive perception systems capable of inferring higher-level semantic information from low-level feature and event information for a given type of multimedia content is a problem that has attracted many researchers' attention in recent years. In this work, we address the problem of automatic interpretation and evolution tracking of a tennis match using standard broadcast video sequences as input data. The use of a hierarchical structure consisting of Hidden Markov Models is proposed. This will take low-level events as its input, and will produce an output where the final state will indicate if the point is to be awarded to one player or another. Using hand-annotated data as input for the classifier described, we have witnessed 100% of the points correctly awarded to the players. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-27868-9_119 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
hidden markov model | Broadcasting,Computer science,Semantic information,Artificial intelligence,Classifier (linguistics),Hidden Markov model,Image sequence,Perception,Machine learning,Semantics,Statistical analysis | Conference |
Volume | ISSN | Citations |
3138 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ilias Kolonias | 1 | 2 | 0.74 |
| William J. Christmas | 2 | 697 | 54.09 |
| J. Kittler | 3 | 14346 | 1465.03 |