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 language | English |
|---|---|
| Title of host publication | 2004 IEEE International Conference on Multimedia and Expo (ICME) |
| Pages | 265-268 |
| Number of pages | 4 |
| Volume | 1 |
| State | Published - Dec 1 2004 |
| Event | 2004 IEEE International Conference on Multimedia and Expo (ICME) - Taipei, Taiwan, Province of China Duration: Jun 27 2004 → Jun 30 2004 |
Other
| Other | 2004 IEEE International Conference on Multimedia and Expo (ICME) |
|---|---|
| Country | Taiwan, Province of China |
| City | Taipei |
| Period | 6/27/04 → 6/30/04 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
A decision tree-based multimodal data mining framework for soccer goal detection. / Chen, Shu Ching; Shyu, Mei-Ling; Chen, Min; Zhang, Chengcui.
2004 IEEE International Conference on Multimedia and Expo (ICME). Vol. 1 2004. p. 265-268.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A decision tree-based multimodal data mining framework for soccer goal detection
AU - Chen, Shu Ching
AU - Shyu, Mei-Ling
AU - Chen, Min
AU - Zhang, Chengcui
PY - 2004/12/1
Y1 - 2004/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=11244294681&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=11244294681&partnerID=8YFLogxK
M3 - Conference contribution
SN - 0780386035
SN - 9780780386037
VL - 1
SP - 265
EP - 268
BT - 2004 IEEE International Conference on Multimedia and Expo (ICME)
ER -