@article {Becker-et-al-13a,
	title = {Variational Recursive Joint Estimation of Dense Scene Structure and Camera Motion from Monocular High Speed Traffic Sequences},
	journal = {International Journal of Computer Vision},
	volume = {105},
	year = {2013},
	pages = {269{\textendash}297},
	publisher = {Springer US},
	keywords = {Dense depth map, Recursive formulation, Structure from motion, Variational approach},
	issn = {0920-5691},
	doi = {10.1007/s11263-013-0639-7},
	url = {http://dx.doi.org/10.1007/s11263-013-0639-7},
	author = {Florian Becker and Lenzen, Frank and Kappes, J{\"o}rg H. and Christoph Schn{\"o}rr}
}
@article {Rother2002a,
	title = {Linear multi view reconstruction and camera recovery using a reference plane},
	journal = {International Journal of Computer Vision},
	volume = {49},
	number = {2-3},
	year = {2002},
	pages = {117{\textendash}141},
	abstract = {This paper presents a linear algorithm for simultaneous computation of 3D points and camera positions from multiple perspective views based on having a reference plane visible in all views. The reconstruction and camera recovery is achieved in a single step by finding the null-space of a matrix built from image data using Singular Value Decomposition. Contrary to factorization algorithms this approach does not need to have all points visible in all views. This paper investigates two reference plane configurations: Finite reference planes defined by four coplanar points and infinite reference planes defined by vanishing points. A further contribution of this paper is the study of critical configurations for configurations with four coplanar points. By simultaneously reconstructing points and views we can exploit the numerical stabilizing effect of having wide spread cameras with large mutual baselines. This is demonstrated by reconstructing the outside and inside (courtyard) of a building on the basis of 35 views in one single Singular Value Decomposition.},
	keywords = {Critical configurations, Duality, Missing data, Multiple views, Planar parallax, Projective reconstruction, Reference plane, Structure from motion},
	issn = {09205691},
	doi = {10.1023/A:1020189404787},
	author = {Carsten Rother and Carlsson, Stefan}
}
@conference {Rother2002b,
	title = {Linear multi view reconstruction with missing data},
	booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {2351},
	year = {2002},
	pages = {209{\textendash}324},
	abstract = {General multi view reconstruction from affine or projective cameras has so far been solved most efficiently using methods of factorizing image data matrices into camera and scene parameters. This can be done directly for affine cameras [18] and after computing epipolar geometry for projective cameras [17]. A notorious problem has been the fact that these factorization methods require all points to be visible in all views. This paper presents alternative algorithms for general affine and projective views of multiple points where a) points and camera centers are computed as the nullspace of one linear system constructed from all the image data b) only three points have to be visible in all views. The latter requirement increases the flexibility and usefulness of 3D reconstruction from multiple views. In the case of projective views and unknown epipolar geometry, an additional algorithm is presented which initially assumes affine views and compensates iteratively for the perspective effects. In this paper affine cameras are represented in a projective framework which is novel and leads to a unified treatment of parallel and perspective projection in a single framework. The experiments cover a wide range of different camera motions and compare the presented algorithms to factorization methods, including approaches which handle missing data.},
	keywords = {Affine and Projective Cameras, Linear Multiple View Reconstruction, Missing data, Structure from motion},
	isbn = {9783540437444},
	issn = {16113349},
	doi = {10.1007/3-540-47967-8_21},
	author = {Carsten Rother and Carlsson, Stefan}
}
@conference {Rother2001,
	title = {Linear multi view reconstruction and camera recovery},
	booktitle = {Proceedings of the IEEE International Conference on Computer Vision},
	volume = {1},
	number = {3},
	year = {2001},
	pages = {42{\textendash}49},
	abstract = {This paper presents a linear algorithm for the simultaneous computation of 3D points and camera positions from multiple perspective views, based on having four points on a reference plane visible in all views. The reconstruction and camera recovery is achieved, in a single step, by finding the null-space of a matrix using singular value decomposition. Unlike factorization algorithms, the presented algorithm does not require all points to be visible in all views. By simultaneously reconstructing points and views the numerically stabilizing effect of having wide spread cameras with large mutual baselines is exploited. Experimental results are presented for both finite and infinite reference planes. An especially interesting application of this method is the reconstruction of architectural scenes with the reference plane taken as the plane at infinity which is visible via three orthogonal vanishing points. This is demonstrated by reconstructing the outside and inside (courtyard) of a building on the basis of 35 views in one single SVD.},
	keywords = {Critical configurations, Duality, Missing data, Multiple views, Planar parallax, Projective reconstruction, Reference plane, Structure from motion},
	doi = {10.1109/iccv.2001.937497},
	author = {Carsten Rother and Carlsson, Stefan}
}
