Markerless motion capture of man-machine interaction

This work deals with modeling and markerless tracking of athletes interacting with sports gear. In contrast to classical markerless tracking, the interaction with sports gear comes along with joint movement restrictions due to additional constraints: while humans can generally use all their joints,...

Full description

Saved in:
Bibliographic Details
Main Authors: Rosenhahn, B., Schmaltz, C., Brox, T., Weickert, J., Cremers, D., Seidel, H.-P.
Format: Conference Proceeding
Language:English
Subjects:
Biological system modeling
Computer vision
Gears
Humans
Joints
Kinematics
Layout
Man machine systems
Mathematical model
Tracking
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This work deals with modeling and markerless tracking of athletes interacting with sports gear. In contrast to classical markerless tracking, the interaction with sports gear comes along with joint movement restrictions due to additional constraints: while humans can generally use all their joints, interaction with the equipment imposes a coupling between certain joints. A cyclist who performs a cycling pattern is one example: The feet are supposed to stay on the pedals, which are again restricted to move along a circular trajectory in 3D-space. In this paper, we present a markerless motion capture system that takes the lower-dimensional pose manifold into account by modeling the motion restrictions via soft constraints during pose optimization. Experiments with two different models, a cyclist and a snowboarder, demonstrate the applicability of the method. Moreover, we present motion capture results for challenging outdoor scenes including shadows and strong illumination changes.
ISSN:1063-6919
DOI:10.1109/CVPR.2008.4587520