Discriminative optical flow tensor for video semantic analysis
Computer Vision and Image Understanding
Synopsis Alignment: Importing External Text Information for Multi-model Movie Analysis
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Face detection for video summary using illumination-compensation and morphological processing
Pattern Recognition Letters
Personalized retrieval of sports video based on multi-modal analysis and user preference acquisition
Multimedia Tools and Applications
Evaluation of video news classification techniques for automatic content personalisation
International Journal of Advanced Media and Communication
RoleNet: movie analysis from the perspective of social networks
IEEE Transactions on Multimedia - Special issue on integration of context and content
Video news classification for automatic content personalization: a genetic algorithm based approach
Proceedings of the 14th Brazilian Symposium on Multimedia and the Web
Character identification in feature-length films using global face-name matching
IEEE Transactions on Multimedia
A semantic framework for video genre classification and event analysis
Image Communication
Supporting multimedia recommender systems with peer-level annotations
WebMedia '09 Proceedings of the XV Brazilian Symposium on Multimedia and the Web
Digital video scenes identification using audiovisual features
WebMedia '09 Proceedings of the XV Brazilian Symposium on Multimedia and the Web
Bayesian belief network based broadcast sports video indexing
Multimedia Tools and Applications
Two important action scenes detection based on probability neural networks
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Football video segmentation based on video production strategy
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Mining movie archives for song sequences
Multimedia Tools and Applications
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A content-based movie parsing and indexing approach is presented; it analyzes both audio and visual sources and accounts for their interrelations to extract high-level semantic cues. Specifically, the goal of this work is to extract meaningful movie events and assign them semantic labels for the purpose of content indexing. Three types of key events, namely, 2-speaker dialogs, multiple-speaker dialogs, and hybrid events, are considered. Moreover, speakers present in the detected movie dialogs are further identified based on the audio source parsing. The obtained audio and visual cues are then integrated to index the movie content. Our experiments have shown that an effective integration of the audio and visual sources can lead to a higher level of video content understanding, abstraction and indexing.