Learning-Based Interactive Video Retrieval System

This paper presents an interactive video event retrieval system based on improved adaboost learning. This system consists of three main steps. Firstly, a long video sequence is partitioned into several video clips by using a distribution-based approach instead of detecting shot transition boundaries...

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Bibliographic Details
Published in2006 IEEE International Conference on Multimedia and Expo pp. 1785 - 1788
Main Authors Chi-Jiunn Wu, Hui-Chi Zeng, Szu-Hao Huang, Shang-Hong Lai, Wen-Hao Wang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2006
Subjects
Content based retrieval
Data mining
Feature extraction
Feedback
Gunshot detection systems
Histograms
Information retrieval
Partitioning algorithms
Spatial databases
Video sequences
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Summary:This paper presents an interactive video event retrieval system based on improved adaboost learning. This system consists of three main steps. Firstly, a long video sequence is partitioned into several video clips by using a distribution-based approach instead of detecting shot transition boundaries. Secondly, audiovisual features (i.e., color, motion and audio features) are extracted from video sequences for video clip representation. Finally, the modified AdaBoost learning algorithm is employed for interactive video retrieval with relevance feedback. This AdaBoost learning algorithm differs from conventional AdaBoost learning methods mainly in the selection of paired video features for the weak classifiers. Experimental results show improved performance of video retrieval by using the proposed system
ISSN:1945-7871
1945-788X
DOI:10.1109/ICME.2006.262898