Content-based video similarity model
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
VisualGREP: A Systematic Method to Compare and RetrieveVideo Sequences
Multimedia Tools and Applications
Clip-based similarity measure for hierarchical video retrieval
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Video genre classification using dynamics
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Fuzzy color-based approach for understanding animated movies content in the indexing task
Journal on Image and Video Processing - Color in Image and Video Processing
Parallel neural networks for multimodal video genre classification
Multimedia Tools and Applications
Audiovisual integration for racquet sports video retrieval
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Semantic Image and Video Indexing in Broad Domains
IEEE Transactions on Multimedia
Automatic Video Classification: A Survey of the Literature
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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When considering the quantity of multimedia content that people and professionals accumulate day by day on their storage devices, the necessity of appropriate intelligent tools for searching or navigating, becomes an issue. Nevertheless, the richness of such media is difficult to handle with today's video analysis algorithm. In this context, we propose a similarity measure dedicated to animation movies. This measure is based on the fuzzy fusion of low level descriptors. We focus on the use of a Choquet Integral based fuzzy approach which is proved to be a good solution to take into account complementarity or conflict between fused data and so to model a human like similarity measure. Subjective tests with human observers have been carried out to validate the model.