Paper Info
Title
Shot Classification of Basketball Videos and its Application in Shooting Position Extraction
Abstract
In this paper, we propose a system that can automatically segment a basketball video into several clips on the basis of a GOP-based scene change detection method. The length of each clip and the number of dominant color pixels of each frame are used to classify shots into close-up view, medium view, and full court view. Full court view shots are chosen to do advanced analyses such as ball tracking and parameter extracting for the transformation from a 3D real-world court to a 2D image. After that, we map points in the 2D image to the corresponding coordinates in a real-world court by some physical properties of the 3D shooting trajectory, and compute the statistics of all shooting positions. Eventually we can obtain the information about the most possible shooting positions of a professional basketball team, which is useful for opponents to adopt appropriate defense tactics.
Year
DOI
Venue
2007
10.1109/ICASSP.2007.366100
ICASSP (1)
Keywords
Field
DocType
dominant color,video signal processing,ball tracking,color pixels,shot classification,image resolution,gop-based scene change detection method,3d shooting trajectory,scene change detection,3d real-world court,image classification,tracking,basketball videos,parameter extracting,shooting position extraction,camera calibration,image colour analysis,trajectory,calibration,physical properties,games,layout,application software,data mining
Computer vision,Change detection,Pattern recognition,Computer science,Camera resectioning,Artificial intelligence,Pixel,Contextual image classification,Application software,Image resolution,Trajectory,Basketball
Conference
Volume
ISSN
ISBN
1
1520-6149
1-4244-0727-3
Citations 
PageRank 
References 
13
0.68
1
Authors
5
Name
Order
Citations
PageRank
Ming-chun Tien11337.65
Hua-Tsung Chen228928.72
Yi-Wen Chen31196.80
Ming-Ho Hsiao4495.13
Suh-Yin Lee51596319.67