Adaptive Multimedia Retrieval:User, Context, and Feedback

This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Adaptive Multimedia Retrieval, AMR 2006, held in Geneva, Switzerland in July 2006. The papers cover ontology-based retrieval and annotation, ranking and similarity measurements, music information retrieval, visual modeling, adaptive retrieval, structuring multimedia, as well as user integration and profiling.

Inhalt

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.