Translator Disclaimer
17 November 1995 Accurate and robust stereovision with a large number of aerial images
Author Affiliations +
Automatic computation of 3D reconstruction of scenes is traditionally based on the use of the normalized cross-correlation technique to match stereoscopic images. This matching technique called area-based matching technique allows to retrieve which pixels on images are the projection of the same 3D point of the analyzed scene. In the case of high resolution stereoscopic images which include a ground resolution up to a few decimeters, the matching problem is more difficult because of the presence shadow areas, hidden parts, important discontinuities in the 3D structures and textureless or repetitive-texture regions. These characteristics of high resolution stereoscopic images appear as real obstacles to the area-based matching technique with binocular stereovision approach. In this paper, we present a novel method to compare a dense scene 3D reconstruction from a large number of aerial images. It achieves robust and accurate reconstruction and deals with local occlusions and surface discontinuities. The principle of the algorithm is based on the simultaneous matching of images with a cross-correlation technique. The location of each cameras is unconstrained and a calibration stage is used to retrieve the epipolar geometry. We finally show the feasibility of this approach to produce robust and accurate matchings on results achieved with synthetic and real images.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
D. Canu, Nicholas Ayache, and J. A. Sirat "Accurate and robust stereovision with a large number of aerial images", Proc. SPIE 2579, Image and Signal Processing for Remote Sensing II, (17 November 1995);

Back to Top