Volume 23, Issue 2, May 2016, Pages 233–242
M. Archana1 and M. Kalaiselvi Geetha2
1 Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University., India
2 Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University., India
Original language: English
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
An identifying event in sports video has many efforts of sports applications. In this paper, proposed a system for automatic detection of key events in Broadcast Tennis Video (BTV). The ultimate goal is to detect the events of complete tennis match. The detected tennis events are fault, rally and net approach, there are also other events in BTV, they all are considered as secondary one. To detect the events of tennis by analyzing the player`s position and ball tracking. The experiments done in different tennis tournament, which has the events (fault, rally and net approach), the some of the visual features are extracted from MHI (Motion History Image) and modelled by Support Vector Machines (SVM) and Hidden Markov Model (HMM) for recognizing tennis events. In result HMM gives a higher accuracy rate of 96.66% when compared to SVM rate of 86.42%.
Author Keywords: Ball trajectory, event detection and classification, MHI (Motion History Image).
M. Archana1 and M. Kalaiselvi Geetha2
1 Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University., India
2 Department of Computer Science and Engineering, Faculty of Engineering and Technology, Annamalai University., India
Original language: English
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
An identifying event in sports video has many efforts of sports applications. In this paper, proposed a system for automatic detection of key events in Broadcast Tennis Video (BTV). The ultimate goal is to detect the events of complete tennis match. The detected tennis events are fault, rally and net approach, there are also other events in BTV, they all are considered as secondary one. To detect the events of tennis by analyzing the player`s position and ball tracking. The experiments done in different tennis tournament, which has the events (fault, rally and net approach), the some of the visual features are extracted from MHI (Motion History Image) and modelled by Support Vector Machines (SVM) and Hidden Markov Model (HMM) for recognizing tennis events. In result HMM gives a higher accuracy rate of 96.66% when compared to SVM rate of 86.42%.
Author Keywords: Ball trajectory, event detection and classification, MHI (Motion History Image).
How to Cite this Article
M. Archana and M. Kalaiselvi Geetha, “Automatic Event Detection and Classification Based on Ball Trajectory in Broadcast Tennis Video Using SVM and HMM,” International Journal of Innovation and Scientific Research, vol. 23, no. 2, pp. 233–242, May 2016.
