The acousticvisual emotion guassians model for automatic generation of music video

Ju Chiang Wang*, Yi Hsuan Yang, I. Hong Jhuo, Yen-Yu Lin, Hsin Min Wang

*此作品的通信作者

研究成果: Conference contribution同行評審

25 引文 斯高帕斯(Scopus)

摘要

This paper presents a novel content-based system that utilizes the perceived emotion of multimedia content as a bridge to connect music and video. Specifically, we propose a novel machine learning framework, called Acousticvisual Emotion Guassians (AVEG), to jointly learn the tripartite relationship among music, video, and emotion from an emotion-annotated corpus of music videos. For a music piece (or a video sequence), the AVEG model is applied to predict its emotion distribution in a stochastic emotion space from the corresponding low-level acoustic (resp. visual) features. Finally, music and video are matched by measuring the similarity between the two corresponding emotion distributions, based on a distance measure such as KL divergence.

原文English
主出版物標題MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
頁面1379-1380
頁數2
DOIs
出版狀態Published - 26 12月 2012
事件20th ACM International Conference on Multimedia, MM 2012 - Nara, Japan
持續時間: 29 10月 20122 11月 2012

出版系列

名字MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia

Conference

Conference20th ACM International Conference on Multimedia, MM 2012
國家/地區Japan
城市Nara
期間29/10/122/11/12

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