A decision tree-based multimodal data mining framework for soccer goal detection

Shu Ching Chen, Mei Ling Shyu, Min Chen, Chengcui Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

51 Scopus citations

Abstract

In this paper, we propose a new multimedia data mining framework for the extraction of soccer goal events in soccer videos by using combined multimodal analysis and decision tree logic. The extracted events can be used to index the soccer videos. We first adopt an advanced video shot detection method to produce shot boundaries and some important visual features. Then the visual/audio features are extracted for each shot at different granularities. This rich multi-modal feature set is filtered by a pre-filtering step to clean the noise as well as to reduce the irrelevant data. A decision tree model is built upon the cleaned data set and is used to classify the goal shots. Finally, the experimental results demonstrate the effectiveness of our framework for soccer goal extraction.

Original languageEnglish (US)
Title of host publication2004 IEEE International Conference on Multimedia and Expo (ICME)
Pages265-268
Number of pages4
StatePublished - Dec 1 2004
Event2004 IEEE International Conference on Multimedia and Expo (ICME) - Taipei, Taiwan, Province of China
Duration: Jun 27 2004Jun 30 2004

Publication series

Name2004 IEEE International Conference on Multimedia and Expo (ICME)
Volume1

Other

Other2004 IEEE International Conference on Multimedia and Expo (ICME)
CountryTaiwan, Province of China
CityTaipei
Period6/27/046/30/04

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Chen, S. C., Shyu, M. L., Chen, M., & Zhang, C. (2004). A decision tree-based multimodal data mining framework for soccer goal detection. In 2004 IEEE International Conference on Multimedia and Expo (ICME) (pp. 265-268). (2004 IEEE International Conference on Multimedia and Expo (ICME); Vol. 1).