Title :
A framework for recovering affine transforms using points, lines or image brightnesses
Author_Institution :
Dept. of Comput. Sci., Massachusetts Univ., Amherst, MA, USA
Abstract :
Image deformations due to the relative motion between an observer and an object may be used to infer 3D structure. Up to first order, these deformations can be written in terms of an affine transform. A new framework for measuring affine transforms, which correctly handles the problem of corresponding deformed patches, is presented. In this framework, points, lines or image brightnesses may be used to derive the affine transform between image patches. No correspondence is required. The patches are filtered using Gaussians and derivatives of Gaussians, and the filters are deformed according to the affine transform. The problem of finding the affine transform is therefore reduced to that of finding the appropriate deformed filter to use. The method is local and can handle large affine deformations. Experiments demonstrate that this technique can find scale changes and optical flow in situations where other methods fail
Keywords :
brightness; computational geometry; deformation; filtering and prediction theory; image reconstruction; motion estimation; 3D structure inference; Gaussian derivative filter; Gaussian filter; affine transform recovery; deformed filter; deformed patches; first order deformations; image brightness; image deformations; lines; local method; optical flow; points; relative motion; scale changes; Computational geometry; Filtering; Image motion analysis; Image reconstruction;
Conference_Titel :
Computer Vision and Pattern Recognition, 1994. Proceedings CVPR '94., 1994 IEEE Computer Society Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-8186-5825-8
DOI :
10.1109/CVPR.1994.323821