Multiview specular stereo reconstruction of large mirror surfaces

Balzer, Jonathan; Höfer, Sebastian; Beyerer, Jürgen

doi:10.1109/cvpr.2011.5995346

Cited by 32 publications

(28 citation statements)

References 15 publications

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“…As an alternative, shape recovery can be performed by exploiting multiple reference planes with known pose relative to the camera. This can be achieved either by utilizing multiple views of the object with a reference plane fixed relative to the camera [3,12,2], or with a static camera, but a moving reference plane [4,11]. In [10], it was shown that the surface shape can be recovered from a single viewpoint when two 3D reference points on the light path are known, which is similar to using a moving reference plane.…”

Section: Related Workmentioning

confidence: 97%

Mirror Surface Reconstruction from a Single Image

Liu

Hartley

Salzmann

2013

2013 IEEE Conference on Computer Vision and Pattern Recognition

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This paper tackles the problem of reconstructing the shape of a smooth mirror surface from a single image. In particular, we consider the case where the camera is observing the reflection of a static reference target in the unknown mirror. We first study the reconstruction problem given dense correspondences between 3D points on the reference target and image locations. In such conditions, our differential geometry analysis provides a theoretical proof that the shape of the mirror surface can be uniquely recovered if the pose of the reference target is known. We then relax our assumptions by considering the case where only sparse correspondences are available. In this scenario, we formulate reconstruction as an optimization problem, which can be solved using a nonlinear least-squares method. We demonstrate the effectiveness of our method on both synthetic and real images.

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Section: Related Workmentioning

confidence: 97%

Mirror Surface Reconstruction from a Single Image

Liu

Hartley

Salzmann

2013

2013 IEEE Conference on Computer Vision and Pattern Recognition

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“…A special feature of deflectometric normal fields should be emphasized, namely that their support is truly three-dimensional. Geometric integration methods like ours can deal with this situation, and furthermore, allow for straightforward incorporation of multiple views, see also [38]. Deflectometry is mainly used for industrial online inspection of specular parts Fig.…”

Section: Deflectometrymentioning

confidence: 99%

A Gauss-Newton Method for the Integration of Spatial Normal Fields in Shape Space

Balzer

2011

J Math Imaging Vis

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We address the task of adjusting a surface to a vector field of desired surface normals in space. The described method is entirely geometric in the sense, that it does not depend on a particular parametrization of the surface in question. It amounts to solving a nonlinear least-squares problem in shape space. Previously, the corresponding minimization has been performed by gradient descent, which suffers from slow convergence and susceptibility to local minima. Newton-type methods, although significantly more robust and efficient, have not been attempted as they require second-order Hadamard differentials. These are difficult to compute for the problem of interest and in general fail to be positive-definite symmetric. We propose a novel approximation of the shape Hessian, which is not only rigorously justified but also leads to excellent numerical performance of the actual optimization. Moreover, a remarkable connection to Sobolev flows is exposed. Three other established algorithms from image and geometry processing turn out to be special cases of ours. Our numerical implementation founds on a fast finite-elements formulation on the minimizing sequence of triangulated shapes. A series of examples from a wide range of different applications is discussed to underline flexibility and efficiency of the approach.

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“…The novelty of our work lies in the fact that we do not require a specifically designed calibration target like a checkerboard [7] or a pattern on a calibrated monitor [8,24,14,2,15]. To our knowledge, our paper is the first to present practical results on outdoor reconstruction of specular surfaces.…”

Section: Previous Work and Contributionmentioning

confidence: 99%