Title :
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
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;
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244581
