Paper Info
Title
Extraction and representation of human body for pitching style recognition in broadcast baseball video
Abstract
In baseball games, different release points of pitchers form several kinds of pitching styles. Different pitching styles possess individual advantages. This paper presents a novel pitching style recognition approach for automatic generation of game information and video annotation. First, an effective object segmentation algorithm is designed to compute the body contour and extract the pitcher's body. Then, star skeleton is used as the representative descriptor of the pitcher posture for pitching style recognition. The proposed approach has been tested on broadcast baseball video and the promising experimental results validate the robustness and practicability.
Year
DOI
Venue
2011
10.1109/ICME.2011.6011840
ICME
Keywords
Field
DocType
broadcast baseball video,video annotation,sports video analysis,different release point,style recognition,different pitching style,object segmentation,body contour,baseball game,human body,pitcher posture,style recognition approach,foot,games,trajectory,feature extraction,skeleton
Broadcasting,Computer vision,Pattern recognition,Computer science,Segmentation,sports equipment,Video annotation,Robustness (computer science),Feature extraction,Artificial intelligence,Trajectory
Conference
ISSN
ISBN
Citations 
1945-7871 E-ISBN : 978-1-61284-349-0
978-1-61284-349-0
7
PageRank 
References 
Authors
0.65
12
5
Name
Order
Citations
PageRank
Hua-Tsung Chen128928.72
Chien-Li Chou28610.09
Wen-Jiin Tsai317419.57
Suh-Yin Lee41596319.67
Jen-Yu Yu510412.13