By Topic

Real-time facial pose estimation using eigenspace analysis in a low-dimensional projection-domain image representation

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
$31 $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)
Lange, E. ; Multi-Modal Functions Mitsubishi Lab., Mitsubishi Electr. Corp., Hyogo, Japan ; Kyuma, K.

We introduce eigenspace analysis of image projections and demonstrate that it yields approximately linear representations of facial rotation in the directions up-down and left-right, respectively. The approach uses unsupervised learning-the representation is established even without explicit knowledge of the actual face pose. The method is computationally very inexpensive, as it uses only image projections, a very low-dimensional image representation, and a small number of principal components. In addition, the approach allows us to make effective use of the built-in image projection functions of our artificial retina chips. For a number of applications the method offers thus a fast alternative to more precise and more general, but also more complex methods for determining facial pose

Published in:

Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on  (Volume:2 )

Date of Conference: