Human motion retrieval with symbolic aggregate approXimation

Author

Xiao, Qinkun ; Luo, Yichuang ; Gao, Song

Author_Institution

Dept. of Electron. Eng., Xi´´an Technol. Univ., Xi´´an, China

fYear

2012

fDate

23-25 May 2012

Firstpage

3632

Lastpage

3636

Abstract

Motion capture data exhibits its complexity both spatially and temporally, which makes it a hard work to measure the similarities between human motions. We propose a motion data indexing and retrieval method based on self-organizing map and symbolic aggregate approximation. And the hierarchical clustering method is implemented, which can discover the relationships between different motion types by a binary tree structure. Then the motion motifs of each cluster are extracted for the retrieval of example-based query. The experiment results show the performance of our approach.

Keywords

approximation theory; image motion analysis; image retrieval; indexing; pattern clustering; self-organising feature maps; binary tree structure; example-based query; hierarchical clustering method; human motion retrieval; motion capture data; motion data indexing; retrieval method; self-organizing map; symbolic aggregate approximation; Data mining; Feature extraction; Indexing; Motion segmentation; Time series analysis; Vectors; Hierarchical Clustering; Motion Capture; Retrieval; Self-organizing Map; Symbolic Aggregate approXimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2012 24th Chinese

Conference_Location

Taiyuan

Print_ISBN

978-1-4577-2073-4

Type

conf

DOI

10.1109/CCDC.2012.6244581

Filename

6244581