Title :
Automatic Pitch Type Recognition from Baseball Broadcast Videos
Author :
Takahashi, Masaki ; Fujii, Mahito ; Yagi, Nobuyuki
Author_Institution :
Sci. & Tech. Res. Labs., Japan Broadcasting Corp.
Abstract :
An automatic pitch type recognition system has been developed. It is difficult to determine the pitch type automatically from a baseball broadcast video, so the decision is currently made by specialists that have expertise and experience in baseball. We developed a system incorporating expertise of professionals. The system identifies pitch type, such as straight balls and curveballs, from single-view pitching sequences in a live baseball broadcast. It analyses ball trajectories by using automatic ball tracking and the catcherpsilas stance by tracking the mitt region as well as recognizing the ball speed numbers superimposed on the screen, and it classifies the pitch type using the random forests ensemble-learning algorithm. The system achieved about 90% recognition accuracy in the experiment.
Keywords :
broadcasting; image classification; image sequences; learning (artificial intelligence); random processes; sport; tracking; video signal processing; automatic ball tracking; automatic pitch type recognition system; catcher stance; live baseball broadcast video; mitt region tracking; pitch type classification; random forest ensemble-learning algorithm; single-view pitching sequence; Cameras; Data mining; Digital multimedia broadcasting; Feature extraction; Laboratories; Multimedia communication; Multimedia systems; Shape; Videos; Yagi-Uda antennas; Ensemble learning; Object tracking; Pitch type recognition; Random forests; SIFT features;
Conference_Titel :
Multimedia, 2008. ISM 2008. Tenth IEEE International Symposium on
Conference_Location :
Berkeley, CA
Print_ISBN :
978-0-7695-3454-1
Electronic_ISBN :
978-0-7695-3454-1
DOI :
10.1109/ISM.2008.47