Modeling and learning contact dynamics in human motion

We propose a simple model of human motion as a switching linear dynamical system where the switches correspond to contact forces with the ground. This significantly improves the modeling performance when compared to simpler linear systems, with only marginal increase in complexity. We introduce a no...

Full description

Saved in:
Bibliographic Details
Published in2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 1; pp. 421 - 428 vol. 1
Main Author Bissacco, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Biological system modeling
Computational modeling
Computer science
Computer vision
Humans
Kinematics
Linear systems
Predictive models
Statistics
Switches
Online AccessGet full text

Cover

More Information
Summary:We propose a simple model of human motion as a switching linear dynamical system where the switches correspond to contact forces with the ground. This significantly improves the modeling performance when compared to simpler linear systems, with only marginal increase in complexity. We introduce a novel closed-form (non-iterative) algorithm to estimate the switches and learn the model parameters in between switches. We validate our model qualitatively by running simulations, and quantitatively by computing prediction errors that show significant improvements over previous approaches using linear models.
ISBN:0769523722
9780769523729
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2005.225