Image segmentation and feature extraction for recognizing strokes in tennis game videos


Share/Save/Bookmark

Zivkovic, Z. and Heijden van der, F. and Petkovic, M. and Jonker, W. (2001) Image segmentation and feature extraction for recognizing strokes in tennis game videos. In: Seventh Annual Conference of the Advanced School for Computing and Imaging, ASCI 2001, May 30 - June 1, 2001 , Heijen, The Netherlands.

[img]
Preview
PDF
66Kb
Abstract:This paper addresses the problem of recognizing human actions from video. Particularly, the case of recognizing events in tennis game videos is analyzed. Driven by our domain knowledge, a robust player segmentation algorithm is developed real video data. Further, we introduce a number of novel features to be extracted for our particular application. Different feature combinations are investigated in order to find the optimal one. Finally, recognition results for different classes of tennis strokes using automatic learning capability of Hidden Markov Models (HMMs) are presented. The experimental results demonstrate that our method is close to realizing statistics of tennis games automatically using ordinary TV broadcast videos.
Item Type:Conference or Workshop Item
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:
Link to this item:http://purl.utwente.nl/publications/36135
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page

Metis ID: 200955