By Topic

Object recognition using multiple view invariance based on complex features

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

4 Author(s)

Geometric invariants from multiple views provide useful information for 3D object recognition. However, conventional object recognition methods using invariants based on point features cannot achieve efficient recognition because of large amount of combinations of point features in invariant calculation. To avoid this problem, the authors propose to use more complex features. They adopt arrow junctions and conics as complex features because man-made objects have often trihedral polyhedra (eg. parallelepiped) and circles and they make arrow junctions and conics in images, respectively. The multiple view affine invariance theory can be directly used for arrow junctions. For conics, they propose two types of invariants. They have developed an object recognition method exploiting these invariants. In addition to the recognition method with two input images, they propose a recognition method that needs only a single input image by substituting an image of a target object stored in the model library. Experimental results using 240 pair of images for 24 objects confirm the usefulness of the methods

Published in:

Applications of Computer Vision, 1996. WACV '96., Proceedings 3rd IEEE Workshop on

Date of Conference:

2-4 Dec 1996