1. 1 Preview At least two views are required to access the depth of a scene point and in turn to reconstruct scene structure Multiple views can be obtained by several cameras or by moving a camera Chapter 10: The Geometry of Multiple Views

2. 2 Since and 10.1 Two Views Similarly,

3. 3 10.1.1 Epipolar Geometry

4. 4 ◎ The Calibrated Case -- The intrinsic parameters of cameras are known

5. 5 which relates frames O and O’.

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13. 13 The matrix associated with the rotation whose axis is the unit vector a and whose angle is can be shown to be (Exercise 10.2) Therefore,

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16. 16 ◎ The Uncalibrated Case -- Intrinsic parameters of cameras are unknown

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18. 18 ◎ Estimates based on corresponding points between images

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21. 21 ○ 8-point algorithm (Longuet-Higgins, 1981) 。 Given 8 point correspondences This method does not take advantage of rank = 2

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24. 24 ○ Normalized 8-point algorithm (Hartley, 1995) (1) Translate and scale the image versions of data points so that they are centered at the origin and the average distance to the origin is pixels, (2) Computeby minimizing (3) Enforce the rank-2 constraint using the Luong et al. method

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26. 26 White points: data points White lines: epipolar lines

27. 27 10.2 Three Views ○ Calibrated case:

28. 28 (i) The three constraints are not independent since the three associated planes are intersected at a point P. Any two of them are independent. (ii) The position of a point (say ) can be predicted from the corresponding two points ( ). Each pair of cameras define an epipolar constraint

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31. 31 Image line segment l is the intersection of the plane segment L and the image plane, or is the projection of l onto Plane segment L is formed by the spatial line segment l and the viewpoint O. Consider 10.2.1 Trifocal Geometry

32. 32 Let P(x,y,z) be a point on l, and p and l be their image projections. Then, and where M: 3 by 4 projection matrix, : the equation of plane L. where Rewrite as

33. 33 10.2.2 The Calibrated Case ○ Let the world coordinate system be attached to the first camera. Then, the projection matrices

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35. 35 Their determinants:

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37. 37 Combine the above determinants into a vector The fourth minor: The fourth determinant:

38. 38 ○ Trilinear Constraints -- All the above determinants are zero because of degeneration of

39. 39 10.2.3 The Uncalibrated Case

40. 40 。 The projection matrices 。 Trilinear constraints 10.2.4 Estimation of the Trifocal Tensor ○ The three matrix define the trifocal tensor with 27 coefficients. (calibrated)

41. 41 (1) Estimate the trifocal tensor G from point and line correspondences (a) Each triple of matching points provides 4 independent linear equations (b) Each triple of matching lines provides 2 independent linear equations e.g., p points and l lines, (2) Improve the numerical stability of tensor estimation by normalizing image coordinates of points and lines and the trifocal tensor have 5, 7 and 18 independent coefficients, respectively.

42. 42 10.3 More Views From

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48. 48 Each quadrilinearity expresses the four associated planes intersecting at a point