Adaptive Multimedia Retrieval: User, Context, and Feedback

Marchand-Maillet, Stéphane.

Adaptive Multimedia Retrieval: User, Context, and Feedback 4th International Workshop, AMR 2006, Geneva, Switzerland, July 27-28, 2006, Revised Selected Papers / [electronic resource] : edited by Stéphane Marchand-Maillet, Eric Bruno, Andreas Nürnberger, Marcin Detyniecki. - XII, 276 p. online resource. - Lecture Notes in Computer Science, 4398 0302-9743 ; . - Lecture Notes in Computer Science, 4398 .

Ontology-Based Retrieval and Annotation -- A Method for Processing the Natural Language Query in Ontology-Based Image Retrieval System -- SAFIRE: Towards Standardized Semantic Rich Image Annotation -- Ontology-Supported Video Modeling and Retrieval -- Ranking and Similarity Measurements -- Learning to Retrieve Images from Text Queries with a Discriminative Model -- A General Principled Method for Image Similarity Validation -- Rank-Test Similarity Measure Between Video Segments for Local Descriptors -- Music Information Retrieval -- Can Humans Benefit from Music Information Retrieval? -- Visual Modelling -- A New Approach to Probabilistic Image Modeling with Multidimensional Hidden Markov Models -- 3D Face Recognition by Modeling the Arrangement of Concave and Convex Regions -- Fuzzy Semantic Action and Color Characterization of Animation Movies in the Video Indexing Task Context -- Retrieval of Document Images Based on Page Layout Similarity -- Adaptive Retrieval -- Multimedia Content Adaptation Within the CAIN Framework Via Constraints Satisfaction and Optimization -- Aspects of Adaptivity in P2P Information Retrieval -- Interactive Museum Guide: Accurate Retrieval of Object Descriptions -- Structuring Multimedia -- Semantic Image Retrieval Using Region-Based Relevance Feedback -- Image Retrieval with Segmentation-Based Query -- Fast Structuring of Large Television Streams Using Program Guides -- User Integration and Profiling -- Variation of Relevance Assessments for Medical Image Retrieval -- An Efficient Collaborative Information Retrieval System by Incorporating the User Profile -- The Potential of User Feedback Through the Iterative Refining of Queries in an Image Retrieval System.

9783540715450

10.1007/978-3-540-71545-0 doi


Computer science.
Information storage and retrieval systems.
Information systems.
Multimedia systems.
Artificial intelligence.
Computer vision.
Computer Science.
Information Storage and Retrieval.
Multimedia Information Systems.
Information Systems Applications (incl.Internet).
Image Processing and Computer Vision.
Artificial Intelligence (incl. Robotics).

QA75.5-76.95

025.04

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