Abstract
Video offers solutions to many of the traditional problems with coach, trainer, commenter, umpires and other security issues of modern team games. This paper presents a novel framework to perform player identification and tracking technique for the sports (Kabaddi) with extending the implementation towards the event handling process which expands the game analysis of the third umpire assessment. In the proposed methodology, video preprocessing has done with Kalman Filtering (KF) technique. Extended Gaussian Mixture Model (EGMM) implemented to detect the object occlusions and player labeling. Morphological operations have given the more genuine results on player detection on the spatial domain by applying the silhouette spot model. Team localization and player tracking has done with Robust Color Table (RCT) model generation to classify each team members. Hough Grid Transformation (HGT) and Region of Interest (RoI) method has applied for background annotation process. Through which each court line tracing and labeling in the half of the court with respect to their state-of-art for foremost event handling process is performed. Extensive experiments have been conducted on real time video samples to meet out the all the challenging aspects. Proposed algorithm tested on both Self Developed Video (SDV) data and Real Time Video (RTV) with dynamic background for the greater tracking accuracy and performance measures in the different state of video samples.
Highlights
For eternity sports video plead to large audiences
The BG segmentation and the line detection are mapped with FG evaluation process implemented by Robust Color Table (RCT) method
On these sophisticated data set preprocessing and occlusion handling has done by Extended Gaussian Mixture Model (EGMM) and Kalman Filtering (KF) technique
Summary
Many researchers have worked on improving sports video content annotation with domain specific issues in the past. The proposed work has followed the team game of more than 7 players like basket ball, soccer video and football. Much work has done on these three games in literature. The most relevant work for the team localization and player tracking methodologies are studied and reviewed as follows. Jia Liu et al [1] proposed automatic player detection, labeling and efficient tracking in broadcast soccer video
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
