An efficient pitch-by-pitch extraction algorithm through multimodal information

Kai Lung Hua, Chao Ting Lai, Chuang Wen You*, Wen-Huang Cheng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Sport video analysis facilitates the discovery of semantic structures in sport broadcast videos and enables a wide spectrum of applications. For example, coaches can analyze offensive and defensive plays performed during games to assess a team's capabilities. In general, identifying interested shots, e.g. pitch shots, from broadcast baseball videos requires great human labor to browse through those videos. In this work, we proposed a novel technique that automatically extracts pitch-by-pitch shots by recognizing the reliable emergence of pitching speed displayed on the scoreboard, estimating when and where the pitcher is present, and identifying the pitch shots based on the pitcher's motion degree. To validate the performance and accuracy of the proposed technique, we collected a dataset of baseball videos broadcasted in various countries. The experimental results verify that the proposed technique successfully extracts the desired pitch-by-pitch videos. Furthermore, it outperforms the state-of-the-art approach in terms of accuracy and time complexity.

Original languageEnglish
Pages (from-to)64-77
Number of pages14
JournalInformation sciences
Volume294
DOIs
StatePublished - 10 Feb 2015

Keywords

  • Baseball videos
  • Multi-modal analysis
  • Pitch-by-pitch events
  • Video understanding

Fingerprint Dive into the research topics of 'An efficient pitch-by-pitch extraction algorithm through multimodal information'. Together they form a unique fingerprint.

Cite this