Adaptive Multimedia Retrieval. Large-Scale Multimedia Retrieval and Evaluation
9th International Workshop, AMR 2011, Barcelona, Spain, July 18-19, 2011, Revised Selected Papers
Published on 15. March 2013
Book
Paperback/Softback
X, 141 pages
978-3-642-37424-1 (ISBN)
Description
This book constitutes the refereed post-proceedings of the 9th International Conference on Adaptive Multimedia Retrieval, AMR 2011, held in Barcelona, Spain, in July 2011. The 9 revised full papers and the invited contribution presented were carefully reviewed and selected from numerous submissions. The papers cover topics ranging from theoretical work to practical implementations and its evaluation, most of them dealing with audio or music media. They are organized in topical sections on evaluation and user studies, audio and music, image retrieval, and similarity and music.
More details
Series
Edition
2013 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
43 s/w Abbildungen
X, 141 p. 43 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 9 mm
Weight
242 gr
ISBN-13
978-3-642-37424-1 (9783642374241)
DOI
10.1007/978-3-642-37425-8
Schweitzer Classification
Other editions
Additional editions
Marcin Detyniecki | Ana García-Serrano | Andreas Nürnberger
Adaptive Multimedia Retrieval. Large-Scale Multimedia Retrieval and Evaluation
9th International Workshop, AMR 2011, Barcelona, Spain, July 18-19, 2011, Revised Selected Papers
E-Book
03/2013
Springer
€48.14
Available for download
Content
Learning-Based Interactive Retrieval in Large-Scale Multimedia.- A User Study of Visual Search Performance with Interactive 2D and 3D Storyboards.- An Illustrated Methodology for Evaluating ASR Systems.- Context-Aware Features for Singing Voice Detection in Polyphonic Music.- Personalization in Multimodal Music Retrieval.- Classifying Images at Scene Level: Comparing Global and Local Descriptors.- Effectiveness of ICF Features for Collection-Specific CBIR.- An Experimental Comparison of Similarity Adaptation Approaches.- Combining Sources of Description for Approximating Music Similarity Ratings.- An Approach to Automatic Music Band Member Detection Based on Supervised Learning.