Multiple View Geometry a b c. A. (a,b)→ A. (a,b)→ c f(a,b,c)=0 a b c. (a,b,c)→ (a,b,
c) reconstruct geometry of scene calibrate cameras. Transfer an image point ...
Multiple View Geometry in Computer Vision
Multiple View Geometry A
a
a
c b b
c
f(a,b,c)=0 (a,b)→ A reconstruct geometry of scene (a,b,c)→ (a,b,c) calibrate cameras (a,b)→ c Transfer an image point from one camera to the other
Course objectives • To understand the geometric relations between multiple views of scenes. • To understand the general principles of parameter estimation. • To be able to compute scene and camera properties from real world images using state-of-the-art algorithms.
Applications • MatchMoving
In cinematography, match moving is a visual-effects technique that allows the insertion of computer graphics into live-action footage with correct position, scale, orientation, and motion relative to the photographed objects in the shot. Compute camera motion from video
)
(to register real and virtual object motion
Applications • 3D modeling
Content • Background: Projective geometry (2D, 3D), Parameter estimation, Algorithm evaluation. • Single View: Camera model, Calibration, Single View Geometry. • Two Views: Epipolar Geometry, 3D reconstruction, Computing F, Computing structure, Plane and homographies. • Three Views: Trifocal Tensor, Computing T. • More Views: N-Linearities, Multiple view reconstruction, Bundle adjustment, autocalibration, Dynamic SfM, Cheirality, Duality
Administration • Office hours: Tuesdays 11 to 12 • Grades: • 10% class participation • 20% Matlab homeworks (pending on finding a grader) • 70% project • Proposals due 4 weeks into the semester • Mid term progress report 8 weeks into the semester • Final report and presentation: end of the semester
Relevant textbooks • Computer Vision: A modern approach by Forsyth and Ponce • Multiple view geometry in computer vision by Hartley and Zisserman • An invitation to 3-D Vision; from images to Geometric models by Ma, Soatto, Kosecka and Sastry • The geometry of multiple images by Faugeras and Luong • Introductory techniques for 3D computer vision by Trucco and Verri • Marc Polleyfeys tutorial on 3D reconstruction • http://www.cs.unc.edu/~marc/tutorial.pdf
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