Abstract
In this paper, we propose a new multimedia data mining framework for the extraction of soccer goal events in soccer videos by utilising both 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 multimodal feature set is then filtered by a pre-filtering step in order 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. We also present the experimental results for the proposed framework, which indicate the performance of the framework for soccer goal extraction.
| Original language | English |
|---|---|
| Pages (from-to) | 312-323 |
| Number of pages | 12 |
| Journal | International Journal of Computer Applications in Technology |
| Volume | 27 |
| Issue number | 4 |
| DOIs | |
| State | Published - Dec 1 2006 |
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Keywords
- Multimedia data mining
- Soccer event detection
- Video indexing
ASJC Scopus subject areas
- Computer Science Applications
- Computational Theory and Mathematics
Cite this
A multimodal data mining framework for soccer goal detection based on decision tree logic. / Chen, Shu Ching; Shyu, Mei-Ling; Zhang, Chengcui; Chen, Min.
In: International Journal of Computer Applications in Technology, Vol. 27, No. 4, 01.12.2006, p. 312-323.Research output: Contribution to journal › Article
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TY - JOUR
T1 - A multimodal data mining framework for soccer goal detection based on decision tree logic
AU - Chen, Shu Ching
AU - Shyu, Mei-Ling
AU - Zhang, Chengcui
AU - Chen, Min
PY - 2006/12/1
Y1 - 2006/12/1
N2 - In this paper, we propose a new multimedia data mining framework for the extraction of soccer goal events in soccer videos by utilising both 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 multimodal feature set is then filtered by a pre-filtering step in order 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. We also present the experimental results for the proposed framework, which indicate the performance of the 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 utilising both 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 multimodal feature set is then filtered by a pre-filtering step in order 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. We also present the experimental results for the proposed framework, which indicate the performance of the framework for soccer goal extraction.
KW - Multimedia data mining
KW - Soccer event detection
KW - Video indexing
UR - http://www.scopus.com/inward/record.url?scp=33847120836&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33847120836&partnerID=8YFLogxK
U2 - 10.1504/IJCAT.2006.012001
DO - 10.1504/IJCAT.2006.012001
M3 - Article
VL - 27
SP - 312
EP - 323
JO - International Journal of Computer Applications in Technology
JF - International Journal of Computer Applications in Technology
SN - 0952-8091
IS - 4
ER -