Video Handling with Music and Speech Detection
IEEE MultiMedia
A user attention model for video summarization
Proceedings of the tenth ACM international conference on Multimedia
Video abstraction: A systematic review and classification
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Clever clustering vs. simple speed-up for summarizing rushes
Proceedings of the international workshop on TRECVID video summarization
Latent topic driving model for movie affective scene classification
MM '09 Proceedings of the 17th ACM international conference on Multimedia
IEEE Transactions on Audio, Speech, and Language Processing
Dynamic social network for narrative video analysis
MM '11 Proceedings of the 19th ACM international conference on Multimedia
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This paper presents a content-based movie trailer generation method, named Vid2Trailer (V2T). Since trailers are intended to advertise movies, they must show specific symbols such as the title logo and the main theme music. Moreover, it is expected to attract viewers by its visual and audio content. V2T satisfies these two requirements when creating a trailer from the original movie content. First, the title logo and the main theme music are extracted. Second, impressive speech and video segments are extracted by using an affective content analysis technique. Third, all of the extracted components are concatenated into the form of a trailer; to realize this, we propose a method that estimates the affective impact of shot sequences, and introduce an algorithm that arranges a set of shots so as to maximize the affective impact of the sequence. Experiments show that our V2T is more appropriate to trailer generation than conventional techniques.