Dense 3D reconstruction from images by normal aided matching

Authors:
Zoltán Megyesi;Géza Kós;Dmitry Chetverikov
Affiliations:
Computer and Automation Research Institute, Budapest, Kende u., Hungary and Eötvös Loránd University, Budapest;Computer and Automation Research Institute, Budapest, Kende u., Hungary and Eötvös Loránd University, Budapest;Computer and Automation Research Institute, Budapest, Kende u., Hungary and Eötvös Loránd University, Budapest
Venue:
Machine Graphics & Vision International Journal
Year:
2006

Citing 14
Cited 1

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Abstract

3D models play an increased role in today's computer applications. As a result, there is a need for flexible and easy to use measuring devices that produce 3D models of real world objects. 3D scene reconstruction is a quickly evolving field of computer vision, which aims at creating 3D models from images of a scene. Although many problems of the reconstruction process have been solved, the use of photographs as an information source involves some practical difficulties. Therefore, accurate and dense 3D reconstruction remains a challenging task. We discuss dense matching of surfaces in the case when the images are taken from a wide baseline camera setup. Some recent studies use a region-growing based dense matching framework, and improve accuracy through estimating the apparent distortion by local affine transformations. In this paper we present a way of using pre-calculated calibration data to improve precision. We demonstrate that the new method produces a more accurate model.