By Topic

Dynamic camera self-calibration from controlled motion sequences

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

1 Author(s)
Dron, L. ; MIT Artificial Intelligence Lab., Cambridge, MA, USA

In order to recover camera motion and 3-D structure from a sequence of images, points in the image plane must be related to directions in space. A least-squares algorithm is described for computing camera calibration from a series of motion sequences for which the translational direction of the camera is known. The method does not require special calibration objects or scene structure. It only requires the ability to move the camera in a given direction and to track features in the image as the camera moves. Since it is a linear least-squares method, it can include information from many sequences to produce a robust estimate of the calibration matrix, which can be updated dynamically as new measurements are taken. It uses the most general possible linear model for calibration. Experimental results from applying the algorithm to a set of real motion sequences with noisy correspondence data are given and analyzed

Published in:

Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on

Date of Conference:

15-17 Jun 1993