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Material Type: Notes; Professor: Tappen; Class: COMPUTER VISION; Subject: Computer Applications; University: University of Central Florida; Term: Unknown 1995;
Typology: Study notes
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Lecture 15: Basic Multi-View Geometry
โ If I needed to find out how far point is away from me, I could use triangulation and two views scene pointscene point optical centeroptical center image plane image plane (Graphic from Khurram Shaffique)
โ For the rest of the lecture we will talk about the geometry of multiple views โ To begin we will talk about epipolar geometry (Image from Forsyth and Ponce)
โ The projection of the optical centers of each camera (Image from Forsyth and Ponce) epipole epipole
โ The vectors , , and are coplanar โ Can be expressed as (Image from Forsyth and Ponce)
โ The vector returned by the cross product is perpendicular to the two vectors โ Can be thought of as a normal to a plane โ If the lines in the plane, it should also be perpendicular to that normal (Image from Forsyth and Ponce)
โ Starting with: โ A cross product can be rewritten as a matrix multiplication, leading to the constraint is called the essential matrix
โ The relationship still holds, but we have to calibrate the cameras first. โ Those calibration matrices, combined with the essential matrix are known as the fundamental matrix โ Encodes information from the intrinsic and extrinsic parameters โ Also Rank 2
โ Basic algorithm: 8-point algorithm โ Find 8 corresponding points in the images โ Once you have the corresponding p and p' points, โ Is linear in F c
โ Text also describes the geometry of 3 or more views (From Forsyth and Ponce)
โ It can tell us where to look for points in the other image โ The quantity is a vector โ So, defines a line โ This tells us where to look for the point that corresponds to p โ (Demo) c
โ Interpolate between views to get new view Figure from Dyer and Seitz
Figure from Dyer and Seitz