Abstract
In this paper, an effective multi-concept classifier is proposed for video semantic concept detection. The core of the proposed classifier is a supervised classification approach called C-RSPM (Collateral Representative Subspace Projection Modeling) which is applied to a set of multimodal video features for knowledge discovery. It adoptively selects nonconsecutive principal dimensions to form an accurate modeling of a representative subspace based on the statistical information analysis and thus achieves both promising classification accuracy and operational merits. Its effectiveness is demonstrated by the comparative experiment, as opposed to several wellknown supervised classification approaches including SVM, Decision Trees, Neural Network, Multinomial Logistic Regression Model, and One Rule Classifier, on goal/corner event detection and sports/commercials concepts extraction from soccer videos and TRECVID news collections.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008 |
| Pages | 80-87 |
| Number of pages | 8 |
| DOIs | |
| State | Published - Sep 25 2008 |
| Event | 2nd Annual IEEE International Conference on Semantic Computing, ICSC 2008 - Santa Clara, CA, United States Duration: Aug 4 2008 → Aug 7 2008 |
Other
| Other | 2nd Annual IEEE International Conference on Semantic Computing, ICSC 2008 |
|---|---|
| Country | United States |
| City | Santa Clara, CA |
| Period | 8/4/08 → 8/7/08 |
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ASJC Scopus subject areas
- Artificial Intelligence
- Software
Cite this
An effective multi-concept classifier for video streams. / Chen, Shu Ching; Shyu, Mei-Ling; Chen, Min.
Proceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008. 2008. p. 80-87 4597177.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - An effective multi-concept classifier for video streams
AU - Chen, Shu Ching
AU - Shyu, Mei-Ling
AU - Chen, Min
PY - 2008/9/25
Y1 - 2008/9/25
N2 - In this paper, an effective multi-concept classifier is proposed for video semantic concept detection. The core of the proposed classifier is a supervised classification approach called C-RSPM (Collateral Representative Subspace Projection Modeling) which is applied to a set of multimodal video features for knowledge discovery. It adoptively selects nonconsecutive principal dimensions to form an accurate modeling of a representative subspace based on the statistical information analysis and thus achieves both promising classification accuracy and operational merits. Its effectiveness is demonstrated by the comparative experiment, as opposed to several wellknown supervised classification approaches including SVM, Decision Trees, Neural Network, Multinomial Logistic Regression Model, and One Rule Classifier, on goal/corner event detection and sports/commercials concepts extraction from soccer videos and TRECVID news collections.
AB - In this paper, an effective multi-concept classifier is proposed for video semantic concept detection. The core of the proposed classifier is a supervised classification approach called C-RSPM (Collateral Representative Subspace Projection Modeling) which is applied to a set of multimodal video features for knowledge discovery. It adoptively selects nonconsecutive principal dimensions to form an accurate modeling of a representative subspace based on the statistical information analysis and thus achieves both promising classification accuracy and operational merits. Its effectiveness is demonstrated by the comparative experiment, as opposed to several wellknown supervised classification approaches including SVM, Decision Trees, Neural Network, Multinomial Logistic Regression Model, and One Rule Classifier, on goal/corner event detection and sports/commercials concepts extraction from soccer videos and TRECVID news collections.
UR - http://www.scopus.com/inward/record.url?scp=52149093643&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=52149093643&partnerID=8YFLogxK
U2 - 10.1109/ICSC.2008.72
DO - 10.1109/ICSC.2008.72
M3 - Conference contribution
SN - 9780769532790
SP - 80
EP - 87
BT - Proceedings - IEEE International Conference on Semantic Computing 2008, ICSC 2008
ER -