Paper Info
Title
Analysis of Human Motion, Based on the Reduction of Multidimensional Captured Data --- Application to Hand Gesture Compression, Segmentation and Synthesis
Abstract
This paper describes a method to analyze human motion, based on the reduction of multidimensional captured motion data. A Dynamic Programming Piecewise Linear Approximation model is used to automatically extract in an optimal way key-postures distributed along the motion data. This non uniform sub-sampling can be exploited for motion compression, segmentation, or re-synthesis. It has been applied on arm end-point motion for 3D or 6D trajectories. The analysis method is then evaluated, using an approximation of the curvature and the tangential velocity, which turns out to be robust to noise and can be calculated on multidimensional data.
Year
DOI
Venue
2008
10.1007/978-3-540-70517-8_8
AMDO
Keywords
Field
DocType
human motion,motion compression,multidimensional captured data,arm end-point motion,analysis method,hand gesture compression,piecewise linear approximation model,dynamic programming,tangential velocity,motion data,multidimensional data,non uniform sub-sampling
Computer vision,Data compression ratio,Motion field,Quarter-pixel motion,Curvature,Computer science,Segmentation,Artificial intelligence,Motion analysis,Motion estimation,Data reduction
Conference
Volume
ISSN
Citations 
5098
0302-9743
3
PageRank 
References 
Authors
0.41
12
2
Name
Order
Citations
PageRank
Sylvie Gibet136752.50
Pierre-François Marteau26217.30