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)
Video Annotation for Content-based Retrieval using Human Behavior Analysis and Domain Knowledge
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time view recognition and event detection for sports video
Journal of Visual Communication and Image Representation
Semantic adaptation of sport videos with user-centred performance analysis
IEEE Transactions on Multimedia
Semantic analysis of soccer video using dynamic Bayesian network
IEEE Transactions on Multimedia
Human Behavior Analysis for Highlight Ranking in Broadcast Racket Sports Video
IEEE Transactions on Multimedia
A real time player tracking system for broadcast tennis video
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Detection of tennis court lines for sport video categorization
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part II
Hi-index | 0.00 |
In this paper, we propose a novel algorithm for player detection and tracking in tennis games. The algorithm utilizes court knowledge as well as player color and edge information to extract deformable player figures. Several new techniques are presented in our algorithm: initially, the court lines are detected and reconstructed. Based on the court model, an adaptive search window is designed for locating the minimum region containing a player figure. After retrieving the region of interest, pixel data are processed by non-dominant color extraction and edge detection filters, respectively. Finally, the non-dominant color map and edge map are refined and combined, and a novel shadow removal method is then applied to isolate the player figure. The algorithm was tested on numerous videos with different courts and light condition. Experiments reveal promising results against various environmental factors.