Homography and Image Alignment
Estimating a planar projective map with DLT and SVD, stabilized by Hartley normalization.
Key Terms
HomographyDLTSVDHartley NormalizationWarpingDegeneracy
Python Tools
OpenCVNumPyMatplotlib
Textbook Reference
Szeliski Ch.8Hartley & Zisserman Ch.4
Topics Covered
- 1Planar correspondences and the homography as a projective map
- 2DLT construction and homogeneous least squares via SVD
- 3Hartley normalization and its effect on conditioning
- 4Forward and inverse warping, resampling, and interpolation
- 5Degenerate configurations: collinear points and near-planar scenes
Learning Outcomes
- Derive and solve the DLT system for a homography using SVD
- Apply Hartley normalization and explain why it improves accuracy
- Warp and align images with an estimated homography and detect degeneracy
Lecture Infographics
9 image files
Lecture Infographics
Step-by-step walkthrough · Stage 1 of 7
How a homography is estimated and used
Follow one concrete example from four point pairs to a warped image. Every number shown is computed live from the same data. Use ← → keys or the buttons.
step 1 / 26
Two views of one flat surface · Source view
Camera 1 sees a flat poster head-on. Every pixel lies on the poster plane.
Lecture PDFs
Homography and Image Alignment
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