Random sampling methods for two-view geometry estimation (2007)
Abstract / truncated to 115 words
This thesis treats efficient estimation algorithms for the epipolar geometry, the model underlying two views of the same scene or object. The epipolar geometry is computed from image correspondences that are found by local feature matching. These correspondences are used to calculate the fundamental matrix, which is the mathematical representation of the epipolar geometry. Since there are outliers among the correspondences, the fundamental matrix is usually calculated by the robust RANSAC (RANdom SAmple Consensus) algorithm which is very well suited for this purpose. A disadvantage of the algorithm, however, is that it shows a considerable complexity for higher outlier ratios. This hampers its application in vision algorithms dealing with many views. In this thesis we ...
epipolar geometry – fundamental matrix – robust estimation – random sampling
Information
- Author
- Den Hollander, Richard Jacobus Maria
- Institution
- Delft University of Technology
- Supervisors
- Publication Year
- 2007
- Upload Date
- Sept. 24, 2008
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