Metadata Generation and Distribution for Live Programs on Broadcasting-Telecommunication Linkage Services

Yuko, Konya; Kuwano, Hidetaka; Yamada, Tatsuro; Kawamori, Masahito; Kawazoe, Katsuhiko

doi:10.1007/11581772_20

Cited by 2 publications

(1 citation statement)

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“…Many kinds of metadata on various sports are being distributed in real time via data broad-casting and the Internet (Kon'ya, Kuwano, Yamada, Kawamori, & Kawazoe, 2005;Liddy et al, 2002). For baseball in particular, the data generated for each pitch is diverse and includes player at bat, the count, ball speed, etc.…”

Section: Introductionmentioning

confidence: 99%

Automatic Pitch Type Recognition System from Single-View Video Sequences of Baseball Broadcast Videos

Takahashi¹,

Fujii

Shibata³

et al. 2010

International Journal of Multimedia Data Engineering and Management

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This article describes a system that automatically recognizes individual pitch types like screwballs and sliders in baseball broadcast videos. These decisions are currently made by human specialists in baseball, who are watching the broadcast video of the game. No automatic system has yet been developed for identifying individual pitch types from single view camera images. Techniques using multiple fixed cameras promise highly accurate pitch type identification, but the systems tend to be large. Our system is designed to identify the same pitch types using only the same single-view broadcast baseball videos used by the human specialists, and accordingly we used a number of features, such as the ball’s location, ball speed and catcher’s stance based on the advice of those specialists. The system identifies the pitch type using a classifier trained with the Random Forests ensemble learning algorithm and achieved about 90% recognition accuracy in experiments.

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Section: Introductionmentioning

confidence: 99%