Information Retrieval for Music and Motion

Content-based multimedia retrieval is a challenging research field with many unsolved problems. This monograph details concepts and algorithms for robust and efficient information retrieval of two different types of multimedia data: waveform-based music data and human motion data. It first examines several approaches in music information retrieval, in particular general strategies as well as efficient algorithms. The book then introduces a general and unified framework for motion analysis, retrieval, and classification, highlighting the design of suitable features, the notion of similarity used to compare data streams, and data organization.

Meinard Müller is a Member of the Multimedia Signal Processing Group, Bonn University, working as a Researcher and Assistant Lecturer. His research interests include digital signal processing, multimedia information retrieval, computational group theory, and combinatorics. His special research topics include audio signal processing, computational musicology, analysis of 3D motion capture data, and content-based retrieval in multimedia documents.