Affective classification of movie scenes based on two-pass clustering technique

Che Wei Sung, Yu Chieh Wu, Kun Huang Chien, Jie Chi Yang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

Video-based learning not only provides rich content but also gives multimedia e-learning environment. In this paper, we present an affective movie classification tool, which automatically segments and labels emotion tags for the given video film. Our method integrates nine audio and visual features from each input video. Then the proposed two-pass clustering technique is used to group similar video scenes and gives labels. One good property of our method is that the need of manual annotated training data is un-required. We compared with the other famous algorithms such as ART2 and K-means. The experimental result shows that our video affect classification tool yields better accuracy (recall and precision) than the other clustering approaches. In short, it achieves ∼80% in F-measure rate for 119 testing scenes.

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主出版物標題Workshop Proceedings of the 17th International Conference on Computers in Education, ICCE 2009
頁面60-64
頁數5
出版狀態已出版 - 2009
事件17th International Conference on Computers in Education, ICCE 2009 - Hong Kong, Hong Kong
持續時間: 30 11月 20094 12月 2009

出版系列

名字Workshop Proceedings of the 17th International Conference on Computers in Education, ICCE 2009

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???event.eventtypes.event.conference???17th International Conference on Computers in Education, ICCE 2009
國家/地區Hong Kong
城市Hong Kong
期間30/11/094/12/09

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