Learning-based interactive video retrieval system

Chi Jiunn Wu*, Hui Chi Zeng, Szu-Hao Huang, Shang Hong Lai, Wen Hao Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings
Pages1785-1788
Number of pages4
DOIs
StatePublished - 2006
Event2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Toronto, ON, Canada
Duration: 9 Jul 200612 Jul 2006

Publication series

Name2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings
Volume2006

Conference

Conference2006 IEEE International Conference on Multimedia and Expo, ICME 2006
Country/TerritoryCanada
CityToronto, ON
Period9/07/0612/07/06

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