|Image registration finds a variety of applications in computer vision. Unfortunately, traditional image registration techniques tend to be costly. We present a new image registration technique that makes use of the spatial intensity gradient of the images to find a good match using a type of Newton-Raphson iteration. Our technique is faster because it examines far fewer potential matches between the images than existing techniques. Furthermore, this registration technique can be generalized to handle rotation, scaling and shearing. We show how our technique can be adapted for use in a stereo vision system.
Note: Essentially the same, but shorter version of this paper was presented and included in the Proc. 7th International Joint Conference on Artificial Intelligence (IJCAI) 1981, August 24-28, Vancouver, British Columbia, pp.674-679. When you refer to the work, please refer to the IJCAI paper.
Associated Center(s) / Consortia:
Vision and Autonomous Systems Center
Associated Lab(s) / Group(s): People Image Analysis Consortium
Associated Project(s): Lucas-Kanade 20 Years On
Number of pages: 10
|Bruce D. Lucas and Takeo Kanade, "An Iterative Image Registration Technique with an Application to Stereo Vision (DARPA)," Proceedings of the 1981 DARPA Image Understanding Workshop, April, 1981, pp. 121-130.|
author = "Bruce D. Lucas and Takeo Kanade",
title = "An Iterative Image Registration Technique with an Application to Stereo Vision (DARPA)",
booktitle = "Proceedings of the 1981 DARPA Image Understanding Workshop",
pages = "121-130",
month = "April",
year = "1981",
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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