A system for deductive prediction and analysis of movement of basketball referees
| Autor: | Miodrag Ivkovic, Predrag Pecev, Miloš Racković |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Basketball
Artificial neural network Computer Networks and Communications Computer science business.industry 020207 software engineering 02 engineering and technology Machine learning computer.software_genre Perceptron GeneralLiterature_MISCELLANEOUS Software Hardware and Architecture 0202 electrical engineering electronic engineering information engineering Media Technology Ball (bearing) 020201 artificial intelligence & image processing Artificial intelligence Time series business computer |
| Zdroj: | Multimedia Tools and Applications. 75:16389-16416 |
| ISSN: | 1573-7721 1380-7501 |
| Popis: | This paper presents us with an automatic prediction and analysis of basketball referees movement which is useful for educational software. Such software would be very beneficial in training the young basketball referees. The paper proposes that the movement prediction of basketball referees can be achieved with a multilayered perceptron neural network. Network will reason on the basis of a ball movement during a play action. Proposed neural network will be trained with a modified Back Propagation algorithm which essentially presents a special algorithm for a multiple dependent Time Series prediction. In this paper, we will also describe initial designs of a neural network structure that, we believe, would better suit the nature of a multiple dependent Time Series prediction problems. The aforementioned educational software is capable of determining whether a referee was moving properly in a certain situation or not. Determination is possible on the basis of numerical values that are calculated by simulating the human visual field. The referee's horizontal field of view simulation is based on the standard set by the American Optometric Association. It is implemented through a modified Sweep and Prune algorithm which is also discussed in this paper. |
| Databáze: | OpenAIRE |
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