Multiview Specular Stereo Reconstruction of Large Mirror Surfaces

Conference paper


Jonathan Balzer
Sebastian Höfer
Jürgen Beyerer


Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011.




IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, USA, June 21 - 23, 2011

In deflectometry, the shape of mirror objects is recovered from distorted images of a calibrated scene. While remarkably high accuracies are achievable, state-of-the-art methods suffer from two distinct weaknesses: First, for mainly constructive reasons, these can only capture a few square centimeters of surface area at once. Second, reconstructions are ambiguous i.e. infinitely many surfaces lead to the same visual impression. We resolve both of these problems by introducing the first multiview specular stereo approach, which jointly evaluates a series of overlapping deflectometric images. Two publicly available benchmarks accompany this paper, enabling us to numerically demonstrate viability and practicability of our approach.