By Topic

Pose-Invariant 3D Object Recognition Using Linear Combination of 2D Views and Evolutionary Optimisation

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)
Zografos, V. ; Dept. of Comput. Sci., Univ. Coll. London ; Buxton, Bernard F.

In this work, we present a method for model-based recognition of 3d objects from a small number of 2d intensity images taken from nearby, but otherwise arbitrary viewpoints. Our method works by linearly combining images from two (or more) viewpoints of a 3d object to synthesise novel views of the object. The object is recognised in a target image by matching to such a synthesised, novel view. All that is required is the recovery of the linear combination parameters, and since we are working directly with pixel intensities, we suggest searching the parameter space using an evolutionary optimisation algorithm in order to efficiently recover the optimal parameters and thus recognise the object in the scene

Published in:

Computing: Theory and Applications, 2007. ICCTA '07. International Conference on

Date of Conference:

5-7 March 2007