Automatic Annotation of Tennis Video Sequences
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Automatic Classification of Tennis Video for High-level Content-based Retrieval
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Survey of sports video analysis: research issues and applications
VIP '05 Proceedings of the Pan-Sydney area workshop on Visual information processing
Online Selection of Discriminative Tracking Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Player Detection and Tracking in Broadcast Tennis Video
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
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This paper proposes a novel framework for tennis player detection and tracking. The algorithm is built on (1) a powerful court-line pixel detection method utilizing intensity and texture pattern, (2) a fast RANSAC-based line parameter estimation which also determines line extents, and (3) a player segmentation and tracking algorithm exploiting knowledge of tennis court model. The content of the video is then explored at a highly semantic level. The framework was tested extensively on numerous challenging video sequences with various court environments and lighting conditions. The results show the robustness and the promising direction of our algorithm.