Trajectory Triangulation: 3D Reconstruction of Moving Points from a Monocular Image Sequence
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Fitting of Surfaces to Data with Covariances
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Method for Fitting Parametric and Nonparametric Models to Noisy Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image-Based Rendering Using Parameterized Image Varieties
International Journal of Computer Vision
Bootstrapping Errors-in-Variables Models
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
Camera Calibration and Euclidean Reconstruction from Known Observer Translations
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Application of the Fisher-Rao Metric to Ellipse Detection
International Journal of Computer Vision
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A complete analysis of the statistical issues related to the estimation of a bilinear form, one of the fundamental problems in computer vision, is presented. It is shown why already at moderate noise levels most available techniques fail to provide a satisfactory solution. A new estimation procedure is proposed in which the nonlinear nature of the errors are taken into account and the implementation uses the generalized singular value decomposition for superior numerical behavior. As an example, the ellipse fitting problem is discussed, and the performance of the new algorithm is compared with thecurrent state-of-the-art.