Titlebook: Information Retrieval for Music and Motion; Meinard Müller Textbook 2007 Springer-Verlag Berlin Heidelberg 2007 Analysis.Audio Matching.Mo

值得

Relational Features and Adaptive Segmentationfy and extract user-specified motions. Previous retrieval systems often require manually generated textual annotations, which roughly describe the motions in words. Since the manual generation of reliable and descriptive labels is infeasible for large datasets, one needs efficient . retrieval method

macrophage

暫時(shí)休息

Rinne-Test

MT-Based Motion Annotation and Retrievals of all motions in the class. The application of MTs to automatic motion annotation and retrieval, which is the content of this chapter, is based on the following interpretation: the consistent aspects of a class MT represent the class characteristics that are shared by all motions, whereas the inc

Criteria

ostracize

Obverse

暫停,間歇

DTW-Based Motion Comparison and Retrieval cost or distance matrix that exhibits self-similarities within the motion. In Sect. 10.3, we describe how this idea can be exploited for motion retrieval. Finally, in Sect. 10.4, we discuss some work related to DTW-based motion retrieval.

控訴

使痛苦

Motion Templatescriptive power of motion templates. Finally, in Sect. 13.5, we close with some general remarks on the multiple alignment problem underlying our learning procedure. In this and the following chapter, we close follow Müller and R?der [143]. An accompanying video is available at [144].