Algorithms in invariant theory
Algorithms in invariant theory
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Vanishing Point Detection by Line Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Metric Rectification for Perspective Images of Planes
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Physics-Based 3D Position Analysis of a Soccer Ball from Monocular Image Sequences
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Single view based pose estimation from circle or parallel lines
Pattern Recognition Letters
A new normalized method on line-based homography estimation
Pattern Recognition Letters
Single view metrology from scene constraints
Image and Vision Computing
| Hi-index | 0.00 |
The plane metrology using a single uncalibrated image is studied in the paper, and three novel approaches are proposed. The first, approach, namely key-line-based method, is an improvement over the widely used key-point-based method, which uses line correspondences directly to compute homography between the world plane and its image so as to increase the computational accuracy. The second and third approaches are both based on a pair of vanishing points from two orthogonal sets of parallel lines in the space plane together with two unparallel referential distances, but the two methods deal with the problem in different ways. One is from the algebraic viewpoint which first maps the image points to an affine space via a transformation constructed from the vanishing points, and then computes the metric distance according to the relationship between the affine space and the Euclidean space, while the other is from the geometrical viewpoint based on the invariance of cross ratios. The second and third methods avoid the selection of control points and are widely applicable. In addition, a brief description on how to retrieve other geometrical entities on the space plane, such as distance from a point to a line, angle formed by two lines, etc., is also presented in the paper. Extensive experiments on simulated data as well as on real images show that the first, and the second approaches are of better precision and stronger robustness than the key-point-based one and the third one, since these two approaches are fundamentally based on line information.