Model-based object recognition commonly involves using a minimal set of matched model and image points to compute the pose of the model in image coordinates. Furthermore, recognition systems often rely on the "weak-perspective" imaging model in place of the perspective imaging model. This paper discusses computing the pose of a model from three corresponding points under weak-perspective projection. A new solution to the problem is proposed which, like previous solutions, involves solving a biquadratic equation. Here the biquadratic is motivated geometrically and its solutions, comprised of an actual and a false solution, are interpreted graphically. The final equations take a new form, which lead to a simple expression for the image position of any unmatched model point.
|
1073
|
Random Sample Consensus: A paradigm for model fitting with applications to image analysis and automated cartography
– Fischler, Bolles
- 1981
|
|
415
|
Closed-form solution of absolute orientation using unit quaternions
– Horn
- 1987
|
|
353
|
Recognition by linear combinations of models
– Ullman, Basri
- 1991
|
|
337
|
Generalizing the Hough transform to detect arbitrary shapes
– Ballard
- 1981
|
|
259
|
Geometric hashing: A general and efficient model-based recognition scheme
– Lamdan, Wolfson
- 1988
|
|
203
|
Recognizing solid objects by alignment with an image
– Huttenlocher, Ullman
- 1990
|
|
177
|
The representation, recognition, and locating of 3-d objects
– FAUGERAS
- 1986
|
|
167
|
Machine perception of three-dimensional solids
– Roberts
- 1966
|
|
143
|
Object recognition using alignment
– Huttenlocher, Ullman
- 1987
|
|
135
|
Introduction to Robotics
– Craig
- 1989
|
|
128
|
Aligning pictorial descriptions: an approach to object recognition
– Ullman
- 1989
|
|
114
|
HYPER: A new approach for the recognition and positioning of two-dimensional objects
– Ayache, Faugeras
- 1986
|
|
100
|
Analysis and solutions of the three point perspective pose estimation problem
– Haralick, Lee, et al.
|
|
96
|
Fundamentals of Matrix Computations
– Watkins
- 1991
|
|
95
|
Object Recognition by Affine Invariant Matching
– Lamdan, Schwartz, et al.
- 1988
|
|
89
|
Three-dimensional model matching from an unconstrained viewpoint
– Thompson, Mundy
- 1987
|
|
88
|
On the Sensitivity of the Hough Transform for Object Recognition
– Grimson, Huttenlocher
- 1990
|
|
43
|
Pose Determination of a Three-Dimensional Object Using Triangle Pairs
– Linainmaa, Harwood, et al.
- 1985
|
|
41
|
S.: The alignment of objects with smooth surfaces
– Basri, Ullman
- 1988
|
|
25
|
Geometric hashing: A general and e cient model-based recognition scheme
– Lamdan, Wolfson
- 1988
|
|
23
|
R.A.Volz, Recognizing Partially Occluded Parts
– Turney
- 1985
|
|
22
|
Recognizing 3D Objects from 2D Images: An Error Analysis
– Grimson, Huttenlocher, et al.
- 1992
|
|
22
|
Three-Dimensional Recognition of Solid Objects from a Two-Dimensional Image
– Huttenlocher
- 1988
|
|
21
|
New Methods for Matching 3-D Objects with Single Perspective Views
– Horaud
- 1987
|
|
19
|
Mapping image properties into shape constraints: Skewed symmetry, affine-transformable patterns, and the shape-from-texture paradigm
– Kanade, Kender
- 1983
|
|
17
|
Applications of Tensor Theory to Object Recognition and Orientation Determination
– Cyganski, Orr
- 1985
|
|
16
|
Feature Matching for Object Localization in the Presence of Uncertainty
– Cass
- 1990
|
|
14
|
Object recognition by a ne invariant matching
– Lamdan, Schwartz, et al.
- 1988
|
|
13
|
Optimal Matching of Planar Models in 3D Scenes
– Jacobs
- 1991
|
|
13
|
An Approach to Object Recognition: Aligning Pictorial Descriptions
– Ullman
- 1986
|
|
9
|
Computational Studies in the Interpretation of Structure and Motion: Summary and Extension
– Ullman
- 1983
|
|
2
|
High-accuracy Model Matching for Scenes Containing Man-Made Structures
– Clark, Eckhardt, et al.
- 1979
|
|
2
|
Object Recognition and Orientation Determination by Tensor Methods
– Cyganski, Orr
- 1988
|