J. Alon and S. Sclaroff. Recursive estimation of motion and planar structure. In Proc. CVPR, pages II:550--556, 2000.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....all possible shape models, planes occupy a special place in that the projection of a plane undergoing rigid motion evolves according to a projective transformation. It is, therefore, natural to represent a scene as a collection of planes, which has been done often in the past, as for instance in [2, 26, 32]. Recently, Dellaert et al. 9] proposed a direct method for SFM that poses the problem as finding the maximum likelihood estimate of structure and motion from all possible assignments of threedimensional features to image measurements. In our work we avoid computing directly the correspondences. ....

J. Alon and S. Sclaroff, Recursive estimation of motion and planar structure, IEEE Computer Vision and Pattern Recognition, pp. II:550--556, 2000.

....is a primitive sufficiently general to model a large number of real scenes, especially in man made environments. Moreover, there are several works dealing with planes, that might be useful for an integrated modeling system: plane detection [3, 7, 10, 11, 12, 32, 40] plane guided point matching [1, 11, 12, 32, 45], and self calibration using the knowledge of planes [ 1, 24, 42, 45, 46] 1Note that this is very different from the hybrid approach of [9] which is actually primitive based. Concretely, we propose methods to parameterize points and planes under multi coplanarity constraints. This ....

....especially in man made environments. Moreover, there are several works dealing with planes, that might be useful for an integrated modeling system: plane detection [3, 7, 10, 11, 12, 32, 40] plane guided point matching [1, 11, 12, 32, 45] and self calibration using the knowledge of planes [ 1, 24, 42, 45, 46]. 1Note that this is very different from the hybrid approach of [9] which is actually primitive based. Concretely, we propose methods to parameterize points and planes under multi coplanarity constraints. This parameterization is consistent in the sense that its number of parameters is the same ....

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J. Alon and S. Sclaroff. Recursive estimation of motion and planar structure. Hilton Head Island, South Carolina, USA, pages 550-556, 2000.

....range along a wall, from two different poses. Red peaks are in wall returns, blue are off wall returns. tween rotation and translation motions of the camera. Without range information from stereo, it is impossible to determine camera motion unambiguously, even if the images are aligned visually [14,15,16]. The search is over two rotations and two translations of the camera, and can be computationally expensive. We have found techniques that make this search practical; these techniques isolate individual parameters or parameter pairs for optimization. Unlike standard techniques for ....

J. Alon and S. Sclaroff. Recursive Estimation of Motion and Planar Structure. Proc. IEEE Conf. on Computer Vision and Pattern Recognition, (2000).

....Of all possible shape models, planes occupy a special place in that the projection of a plane undergoing rigid motion evolves according to a projective transformation. It is therefore natural to represent a scene as a collection of planes, which has been done often in the past, as for instance in [40, 36, 35, 44, 3]. We seek to build on the strengths of direct methods, in order to avoid common problems with fea3 ture tracking by embedding the process in higher level motion estimation, while keeping computational complexity at bay representing shape using a collection of simple templates. 1.3 Main ....

J. Alon and S. Sclaroff. Recursive estimation of motion and planar structure. In IEEE Computer Vision and Pattern Recognition, pages II:550--556, 2000.

....be noted here about this process. Ambiguities exist in the alignment process, especially correlation between rotation and translation motions of the camera. Without range information from stereo, it is impossible to determine camera motion unambiguously, even if the images are aligned visually [14,15,16]. The search is over two rotations and two translations of the camera, and can be computationally expensive. We have found techniques that make this search practical; these techniques isolate individual parameters or parameter pairs for optimization. Unlike standard techniques for ....

J. Alon and S. Sclaroff. Recursive Estimation of Motion and Planar Structure. Proc. IEEE Conf. on Computer Vision and Pattern Recognition, (2000).

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J. Alon and S. Sclaroff. Recursive estimation of motion and planar structure. In Proc. CVPR, pages II:550--556, 2000.

....in the sense that they assume no prior knowledge about the scene. However, in practice, the scene typically contains structures with strong geometric regularities that can be used to constrain the estimation problem. Consequently, algorithms have been proposed for the special cases of planes [1, 11, 22, 26, 27, 31], piecewise planar models [3, 19] polygonal meshes [14] and quadric surfaces [8, 18] In this paper we propose a method for reconstructing 3D rational B spline surfaces from multiple views. As will be shown, we can exploit the the projective invariance properties of rational B splines to gain a ....

....into reconstruction methods as well. In particular, the special case of planar structure has been extensively researched, and there are methods that incorporate the resulting constraints [26] In particular [31] has developed a closed form solution to planar reconstruction from two views and [1] had extended the recursive framework of [2] to incorporate planar information. In [19] Sinclair focuses on grouping planar regions, while [3] focuses on direct reconstruction. Some methods segment the scene and determine planes for each patch [11, 22, 27] More general surface representations ....

J. Alon and S. Sclaroff. Recursive estimation of motion and planar structure. In Proc. CVPR, pages II:550--556, 2000.

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J. Alon and S. Sclaroff. Recursive estimation of motion and planar structure. In Proceedings of the Conference on Computer Vision and Pattern Recognition, Hilton Head Island, South Carolina, USA, pages 550--556, 2000.

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