Video Content Analysis Using Multimodal Information: For Movie Content Extraction, Indexing and Representation
RoleNet: movie analysis from the perspective of social networks
IEEE Transactions on Multimedia - Special issue on integration of context and content
A Novel Role-Based Movie Scene Segmentation Method
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Character identification in feature-length films using global face-name matching
IEEE Transactions on Multimedia
A generic framework of user attention model and its application in video summarization
IEEE Transactions on Multimedia
Video scene segmentation using Markov chain Monte Carlo
IEEE Transactions on Multimedia
Video summarization and scene detection by graph modeling
IEEE Transactions on Circuits and Systems for Video Technology
Exploiting content relevance and social relevance for personalized ad recommendation on internet TV
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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A decent movie summary is helpful for movie producer to promote the movie as well as audience to capture the theme of the movie before watching the whole movie. Most exiting automatic movie summarization approaches heavily rely on video content only, which may not deliver ideal result due to the semantic gap between computer calculated low-level features and human used high-level understanding. In this paper, we incorporate script into movie analysis and propose a novel character-based movie summarization approach, which is validated by modern film theory that what actually catches audiences' attention is the character. We first segment scenes in the movie by analysis and alignment of script and movie. Then we conduct substory discovery and content attention analysis based on the scent analysis and character interaction features. Given obtained movie structure and content attention value, we calculate movie attraction scores at both shot and scene levels and adopt this as criterion to generate movie summary. The promising experimental results demonstrate that character analysis is effective for movie summarization and movie content understanding.