Geometric Computer Vision: Difference between revisions

Geometric Computer Vision (view source)

655 bytes added , 11 March 2021

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 y' m_3'^T - m_2'^T\\
 \end{bmatrix}</math>
+===Reconstruction for intrinsically calibrated cameras===
+# Compute the essential matrix E using normalized points
+# Select M=[I|0] M'=[R|T] then E=[T_x]R
+# Find T and R using SVD of E.
+===Reconstruction ambiguity: projective===
+<math>x_h = MX_i = (MH_p^{-1})(H_P X_i)</math>
+* Moving the camera will get a different reconstruction even with the same image. The 3D model will be changed by some homography.
+* If you know 5 points in 3D, you can rectify the 3D model.
+;Projective Reconstruction Theorem
+* We can compute a projective reconstruction of a scene from 2 views.
+* We don't have to know the calibration or poses.
+===Affine Reconstruction===
 ==Projects==