By Topic

A new generalized computational framework for finding object orientation using perspective trihedral angle constraint

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

4 Author(s)
Yuyan Wu ; Dept. of Comput. Sci., Louisiana State Univ., Baton Rouge, LA, USA ; S. S. Iyengar ; R. Jain ; S. Bose

This paper investigates a fundamental problem of determining the position and orientation of a three-dimensional (3-D) object using a single perspective image view. The technique is focused on the interpretation of trihedral angle constraint information. A new closed form solution based on Kanatani's formulation is proposed. The main distinguishing feature of the authors' method over the original Kanatani formulation is that their approach gives an effective closed form solution for a general trihedral angle constraint. The method also provides a general analytic technique for dealing with a class of problem of shape from inverse perspective projection by using “angle to angle correspondence information.” A detailed implementation of the authors' technique is presented. Different trihedral angle configurations were generated using synthetic data for testing the authors' approach of finding object orientation by angle to angle constraint. The authors performed simulation experiments by adding some noise to the synthetic data for evaluating the effectiveness of their method in a real situation. It has been found that the authors' method worked effectively in a noisy environment which confirms that the method is robust in practical application

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:16 ,  Issue: 10 )