Ellipse Constraints for Improved Wide-Baseline Feature Matching and Reconstruction
The classic feature matching process has two drawbacks. Firstly, ambiguous but possibly correct matches will potentially be removed and secondly, there is no constraint for the 2D size of the features.
In the present paper these drawbacks are tackled at once with a different approach: by considering region features instead of point features and by adding constraints based on the features’ shape. Here, the shape will be described with an ellipse. Using existing knowledge about the algebraic properties of ellipses within the computer vision domain, this enables additional constraints such as ellipse tangents. The number of ambiguous matches is reduced and increased control of the physical 2D size of the features is obtained. This will be shown on known epipolar geometry.
Additionally, reconstruction of feature ellipses is examined.
KeywordsKey Points Feature Regions Ellipses Feature Matching Epipolar Constraints Reconstruction
Unable to display preview. Download preview PDF.
- 1.Brown, D.: Close range camera calibration. Photogrammetric Engineering 37, 855–866 (1971)Google Scholar
- 2.Cross, G.: Surface Reconstruction from Image Sequences. PhD thesis, University of Oxford (2000)Google Scholar
- 3.Cross, G., Zisserman, A.: Quadric reconstruction from dual-space geometry. In: Sixth International Conference on Computer Vision, pp. 25–31 (1998)Google Scholar
- 8.Lowe, D.G.: Object recognition from local scale-invariant features. In: IEEE International Conference on Computer Vision, vol. 2, p. 1150. IEEE Computer Society, Los Alamitos (1999)Google Scholar
- 19.Semple, J., Kneebone, G.: Algebraic Projective Geometry. Oxford Classic Texts (1998)Google Scholar
- 20.Weisstein, E.W.: Ellipse. From MathWorld–A Wolfram Web Resource, http://mathworld.wolfram.com/Ellipse.html