Paper Info
Title
Automatic music video summarization based on audio-visual-text analysis and alignment
Abstract
In this paper, we propose a novel approach for automatic music video summarization based on audio-visual-text analysis and alignment. The music video is separated into the music and video tracks. For the music track, the chorus is detected based on music structure analysis. For the video track, we first segment the shots and classify the shots into close-up face shots and non-face shots, then we extract the lyrics and detect the most repeated lyrics from the shots. The music video summary is generated based on the alignment of boundaries of the detected chorus, shot class and the most repeated lyrics from the music video. The experiments on chorus detection, shot classification, and lyrics detection using 20 English music videos are described. Subjective user studies have been conducted to evaluate the quality and effectiveness of summary. The comparisons with the summaries based on our previous method and the manual method indicate that the results of summarization using the proposed method are better at meeting users' expectations.
Year
DOI
Venue
2005
10.1145/1076034.1076097
SIGIR
Keywords
Field
DocType
video track,audio-visual-text analysis,repeated lyric,music track,english music video,manual method,automatic music video summarization,chorus detection,music video summary,music structure analysis,music video,video tracking,summarization,structure analysis,chorus,text analysis
Structure analysis,Automatic summarization,Text mining,Computer science,Speech recognition,Lyrics,Chorus,User studies
Conference
ISBN
Citations 
PageRank 
1-59593-034-5
16
0.84
References 
Authors
22
4
Name
Order
Citations
PageRank
Changsheng Xu14957332.87
Xi Shao222619.08
Namunu C. Maddage334526.51
Mohan Kankanhalli43825299.56