Paper Info
Title
Motion beat induction based on short-term principal component analysis
Abstract
We propose a novel tool called short-term principal component analysis (ST-PCA) to analyze motion capture (MoCap) data, which records realistic movements in a high dimensional time series. Our ST-PCA is successfully applied to beat induction, which is an important perception of human motion especially in dances and is required by many applications such as music synchronization [Kim et al. 2003; Shiratori et al. 2006]. Following [Kim et al. 2003], motion beats are defined as the regular moments when the movement is changed significantly in direction or magnitude. Different from the previous approaches [Kim et al. 2003; Shiratori et al. 2006] that analyze MoCap data in each channel, we estimate the motion beats regarding MoCap data as a whole with the proposed ST-PCA, which performs PCA in a sliding window. Our experiments demonstrate that our method can estimate much more accurate beats in a wide range of motions including complicated dances.
Year
DOI
Venue
2009
10.1145/1667146.1667173
ACM SIGGRAPH ASIA 2009 Sketches
Keywords
DocType
Citations 
human motion,important perception,motion beat,short-term principal component analysis,complicated dance,novel tool,mocap data,high dimensional time series,accurate beat,proposed st-pca,music synchronization,motion capture,principal component analysis,range of motion,wearable computing,augmented reality,sliding window,time series
Conference
0
PageRank 
References 
Authors
0.34
2
3
Name
Order
Citations
PageRank
Jianfeng Xu100.34
Koichi Takagi2798.12
Akio Yoneyama311717.49