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Single View Geometry Course web page: vision.cis.udel.edu/cv April 7, 2003  Lecture 19.

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Presentation on theme: "Single View Geometry Course web page: vision.cis.udel.edu/cv April 7, 2003  Lecture 19."— Presentation transcript:

1 Single View Geometry Course web page: vision.cis.udel.edu/cv April 7, 2003  Lecture 19

2 Announcements Readings... –From Hartley & Zisserman: Chapter 3.1-3.1.1, 3.4.4 describe basis of DLT algorithm that camera calibration lecture referred to Chapters 1-1.4 (skip 1.2.3), 2-2.2.1 are background for today and Wednesday –Criminisi et al.’s “Single View Metrology” for Wednesday But first, conclusion of calibration lecture

3 Outline Homogeneous representation of lines, planes Vanishing points and lines Single view metrology

4 Homogeneous Representation of 2-D Lines A line in a plane is specified by the equation ax + by + c = 0 In vector form, l = (a, b, c) T This is equivalent to k(a, b, c) T for non- zero k, as with homogeneous point coordinates (0, 0, 0) T is undefined for lines

5 Homogeneous Lines: Results Point on line –A 2-D homogeneous point x = (x, y, 1) T is on the line l = (a, b, c) T only when ax + by + c = 0 –We can write this as a dot product: l ¢ x = 0 Intersection of lines –We want a point x that is on both lines l and l’. This would imply that l ¢ x = l’ ¢ x = 0 –Because the cross product is orthogonal to both multiplicands, x = l £ l’ satisfies this requirement and thus defines the point of intersection Line joining points –This is the dual of line intersection, so l = x £ x’

6 The Intersection of Parallel Lines Consider two parallel lines l = (a, b, c) T and l’ = (a, b, c’) T The intersection of these two lines is given by l £ l’ = (b, {a, 0) T This is not a finite point on the plane, but rather an ideal point, or a point at infinity For example, the lines x = 1 and x = 2 are l = (-1, 0, 1) T and l’ = (-1, 0, 2) T, respectively, and their intersection is (0, 1, 0) T –This is the point at infinity in the direction of the Y -axis

7 Line at Infinity All ideal points (x 1, x 2, 0) T lie on a single line called the line at infinity: l 1 = (0, 0, 1) T This can be thought of as the set of all directions in the plane

8 Homogeneous Representation of Planes A plane in 3-D is specified by the equation ax + by + cz + d = 0 In vector form, ¼ = (a, b, c, d) T Analogous to lines, a 3-D homogeneous point x = (x, y, z, 1) T is on the plane ¼ only when ¼ ¢ x = 0 More results: –The intersection of 2 planes is a line –The intersection of 3 planes is a point –By duality, a plane is the join of 3 non-collinear points

9 More 3-D Analogues 3-D lines have various representations –E.g., 4 x 4 Plucker matrices allow straightforward interaction with 3-D homogeneous points and planes Parallel 3-D lines intersect on the plane at infinity ¼ 1 = (0, 0, 0, 1) T at a 3-D ideal point A plane ¼ intersects ¼ 1 in a line which is the 3-D line at infinity l 1 of ¼

10 Vanishing Points & Lines Vanishing point: Finite image projection of ideal point Vanishing line: Image projection of plane’s line at infinity from Hartley & Zisserman

11 Basic method: Detect edges, identify parallel segments, find intersection point But...because of image noise, etc., lines do not intersect at a unique point Computing a Vanishing Point from an Image from Hartley & Zisserman

12 Vanishing Point Estimation Idea: Fit lines independently, then choose point closest to all of them –Not optimal Better approach: Pick vanishing point location which results in best overall fit to lines –E.g., Levenberg-Marquardt minimization of SSD between endpoints of measured line segments and lines radiating from vanishing point from Hartley & Zisserman

13 Vanishing Line Estimation Compute vanishing points for sets of parallel lines in plane (or parallel planes) Then fit line to vanishing points from Hartley & Zisserman

14 Vanishing Points of Lines Parallel to Plane are on Same Vanishing Line from Hartley & Zisserman

15 Single View Metrology Definition: Obtaining information on scene struct- ure (e.g., lengths, areas) from a single image Idea: Use constraints imposed by parallel lines, planes to get measurements up to scale (Criminisi et al., 1999) from Criminisi et al.

16 Metrology Applications: Forensic Science from Criminisi et al. Knowing the height of the phone booth, can we determine the height of the person?

17 Metrology Applications: Virtual Modeling from Criminisi et al. Original image Synthesized view Synthesized view with original camera location


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