Key points are not available for this paper at this time.
A scheme is developed to match range images in an environment where distinctive features are scarce. When each image overlaps with several other images, the match must also be performed at the global level. This is particularly challenging, because of the possibility of bending and compression in range images. The primitives used for local matching contours of constant range which are extracted from data are represented by means of a modified chain-code method. All best matches of pairs of contours are considered tentative until their geometrical implications are evaluated and a consistent majority has emerged. To do global matching a cost function is constructed and minimized. Terms contributing to the cost include violation of local matches as well as compression and bending in range images. The present global scheme is valid for any set of multiple overlapping range images, whether they contain distinctive features or not. This scheme has been used to map the floor of the ocean, where the range data are obtained by a multibeam echo-sounder system.>
Building similarity graph...
Analyzing shared references across papers
Loading...
Behrooz Kamgar-Parsi
Government of the United States of America
James L. Jones
Idaho State University
Azriel Rosenfeld
Razi University
University of Maryland, College Park
Building similarity graph...
Analyzing shared references across papers
Loading...
Kamgar-Parsi et al. (Tue,) studied this question.
synapsesocial.com/papers/6a0f4a0a426db18b04ed1197 — DOI: https://doi.org/10.1109/cvpr.1989.37862