By Topic

Matching 2D image lines to 3D models: Two improvements and a new algorithm

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)
Kamgar-Parsi, B. ; Office of Naval Res., Arlington, VA, USA ; Kamgar-Parsi, B.

We revisit the problem of matching a set of lines in the 2D image to a set of corresponding lines in the 3D model for the following reasons. (a) Existing algorithms that treat lines as infinitely long contain a flaw, namely, the solutions found are not invariant with respect to the choice of the coordinate frame. The source of this flaw is in the way lines are represented. We propose a frame-independent representation for sets of infinite lines that removes the non-invariance flaw. (b) Algorithms for finding the best rigid transform are nonlinear optimizations that are sensitive to initialization and may result in unreliable and expensive solutions. We present a new recipe for initialization that exploits the 3D geometry of the problem and is applicable to all algorithms that perform the matching in the 3D scene. Experiments show that with this initialization all algorithms find the best transform. (c) We present a new efficient matching algorithm that is significantly faster than existing alternatives, since it does not require explicit evaluation of the cost function and its derivatives.

Published in:

Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on

Date of Conference:

20-25 June 2011