Rigidity Checking of 3D Point Correspondences under Perspective Projection
نویسندگان
چکیده
An algorithm is described which rapidly veri es the potential rigidity of three dimensional point correspondences from a pair of two dimensional views under perspective projection. The output of the algorithm is a simple yes or no answer to the question \Could these corresponding points from two views be the projection of a rigid con guration?" Potential applications include 3D object recognition from a single previous view and correspondence matching for stereo or motion over widely separated views. Our analysis begins with the observation that it is often the case that two views cannot provide an accurate structure-frommotion estimate because of ambiguity and ill-conditioning. However, it is argued that an accurate yes/no answer to the rigidity question is possible and experimental results support this assertion with as few as six pairs of corresponding points over a wide range of scene structures and viewing geometries. Rigidity checking veri es point correspondences by using 3D recovery equations as a matching condition. The proposed algorithm improves upon other methods that fall under this approach because it works with as few as six corresponding points under full perspective projection, handles correspondences from widely separated views, makes full use of the disparity of the correspondences, and is integrated with a linear algorithm for 3D recovery due to Kontsevich. The rigidity decision is based on the residual error of an integrated pair of linear and nonlinear structure-from-motion estimators. Results are given for experiments with synthetic and real image data. A complete implementation of this algorithm is being made publicly available.
منابع مشابه
0pt A Three-Point Model-Based Algorithm for Pose Estimation
| In this paper, an iterative algorithm for the model-based P3P pose-estimation problem based on the Gauss-Newton method is described. In this system, correspondences between three noncollinear object points on a rigid body and their subsequent image points under full perspective projection are used to estimate the pose of the object. Both real images and synthetic data have been used to verify...
متن کامل0pt A Real-time Iterative Three-point Model-based Pose-estimation Algorithm
| In this paper, an iterative algorithm for the model-based P3P pose-estimation problem based on the Gauss-Newton method is described. In this system, correspondences between three noncollinear object points on a rigid body and their image points after movement under full perspective projection model are used to estimate the new position and orientation of the object. Both real images and synth...
متن کاملAny Pair of 2D Curves Is Consistent with a 3D
Symmetry has been shown to be a very effective a priori constraint in solving a 3D shape recovery problem. Symmetry is useful in 3D recovery because it is a form of redundancy. There are, however, some fundamental limits to the effectiveness of symmetry. Specifically, given two arbitrary curves in a single 2D image, one can always find a 3D mirror-symmetric interpretation of these curves under ...
متن کاملAny Pair of 2D Curves Is Consistent with a 3D Symmetric Interpretation
Symmetry has been shown to be a very effective a priori constraint in solving a 3D shape recovery problem. Symmetry is useful in 3D recovery because it is a form of redundancy. There are, however, some fundamental limits to the effectiveness of symmetry. Specifically, given two arbitrary curves in a single 2D image, one can always find a 3D mirror-symmetric interpretation of these curves under ...
متن کاملRigid Point Registration with Expectation Conditional Maximization
This paper addresses the issue of matching rigid 3D object points with 2D image points through point registration based on maximum likelihood principle in computer simulated images. Perspective projection is necessary when transforming 3D coordinate into 2D. The problem then recasts into a missing data framework where unknown correspondences are handled via mixture models. Adopting the Expectat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1995