Abstract
In a previous paper we described a system which recursively recovers a super-resolved three dimensional surface model from a set of images of the surface. In that paper we assumed that the camera calibration for each image was known. In this paper we solve two problems. Firstly, if an estimate of the surface is already known, the problem is to calibrate a new image relative to the existing surface model. Secondly, if no surface estimate is available, the relative camera calibration between the images in the set must be estimated. This will allow an initial surface model to be estimated. Results of both types of estimation are given.
Cite
CITATION STYLE
Morris, R. D., Smelyanskiy, V. N., & Cheeseman, P. C. (2001). Matching images to models - Camera calibration for 3-D surface reconstruction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2134, pp. 105–117). Springer Verlag. https://doi.org/10.1007/3-540-44745-8_8
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