Video Annotation System Based on Categorizing and Keyword Labelling

Authors:
Bin Cui;Bei Pan;Heng Tao Shen;Ying Wang;Ce Zhang
Affiliations:
Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, CHINA & School of EECS, Peking University,;Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, CHINA & School of EECS, Peking University,;School of ITEE, University of Queensland, Australia;Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, CHINA & School of EECS, Peking University,;Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, CHINA & School of EECS, Peking University,
Venue:
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
Year:
2009

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Abstract

In this work, we demonstrate an automatic video annotation system which can provide users with the representative keywords for new videos. The system explores the hierarchical concept model and multiple feature model to improve the effectiveness of annotation, which consists of two components: a SVM classifier to ascertain the category; and a multiple feature model to label the keywords. We implement the demo system using the videos downloaded from YouTube. The results show the superiority of our approach.