Automatic Baseball Video Tagging Based on Voice Pattern Prioritization and Recursive Model Localization
| Autor: | Komei Arasawa, Shun Hattori |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Human-Computer Interaction
Prioritization Artificial Intelligence Computer science 020204 information systems Speech recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Recursive model 02 engineering and technology Computer Vision and Pattern Recognition |
| Zdroj: | Journal of Advanced Computational Intelligence and Intelligent Informatics. 21:1262-1279 |
| ISSN: | 1883-8014 1343-0130 |
| DOI: | 10.20965/jaciii.2017.p1262 |
| Popis: | To enable us to select only the specific scenes that we want to watch in a baseball video and personalize its highlights sub-video, we require an Automatic Baseball Video Tagging system that can divide a baseball video into multiple sub-videos per at-bat scene automatically and append tag information relevant to at-bat scenes. Towards developing the system, the previous papers proposed several Tagging algorithms using ball-by-ball textual reports and voice recognition, and tried to refine models for baseball games. To improve its robustness, this paper proposes a novel Tagging method that utilizes multiple kinds of play-by-play comment patterns for voice recognition which represent the situation of at-bat scenes and take their “Priority” into account. In addition, to search for a voice-recognized play-by-play comment on the start/end of at-bat scenes, this paper proposes a novel modelling method called as “Local Modelling,” as well as Global Modelling used by the previous papers. |
| Databáze: | OpenAIRE |
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