By Topic

Torque-based recursive filtering approach to the recovery of 3D articulated motion from image sequences

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
H. Segawa ; Sony Corp., Tokyo, Japan ; T. Totsuka

In this paper we introduce a recursive filtering method to recover the 3D articulated motion from image sequences. In recursive filtering frameworks, the quality of the results heavily depends on the choice of state variables and the determination of the process model; which models a real object whose motion is to be estimated. Our approach employs robotics dynamics into the recursive filtering framework. And the key strategy is to incorporate joint torques into the model state variables. In addition, we assumed the variations of the joint torques are Gaussian noises. We describe how to integrate dynamics equations into Kalman filters, and with the experimental results our method is shown to be effective

Published in:

Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on.  (Volume:2 )

Date of Conference: