Planar homography: accuracy analysis and applications
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Citations
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References
Multiple view geometry in computer vision
Motion and structure from two perspective views: algorithms, error analysis, and error estimation
Image Mosaicing and Super-resolution
A plane measuring device
Error Characterization of the Factorization Method
Related Papers (5)
Frequently Asked Questions (7)
Q2. In what case does the author claim that their solution provides better estimates in two cases?
In [4], the authors claim that their solution provides better estimates in two cases: 1) Relatively small measurement noise levels, or 2) when minimum N = 4 image correspondences are utilized in the estimation of the homography.
Q3. What are the limitations of the analysis?
Computation of projective homography from frame-to-frame correspondences has been extensively studied in recent years [5], and analytical uncertainty bounds of the homography parameters and reprojection errors have been proposed [4].
Q4. What is the error bound for the envelops?
The dashed blue envelop is the ±3σ error bound computed experimentally, and the other two envelops in green and red are derived from analytical bounds ±3σhc and ±3σho, respectively.
Q5. What is the covariance of the homography?
The authors construct matching pairs {p, p′} based on a pre-specified homographyH; the authors use the well-know interpretation H = R + tnT in terms of the motion {R, t} of a camera relative to a planar scene with surface normal n = [−P,−Q, 1]/Zo, where P and Q control the surface slant and tilt angles, and Zo its distance from the camera.
Q6. How do the authors determine the covariance of the homography parameters?
For small variations –max{δqi} << 1, where qi denotes i-th element of q –it can be shown [6, 7] that up to first-order, the eigenvalues and eigenvectors ofQ vary according to δλi =
Q7. What is the purpose of this paper?
Ability to not only estimate the transformation between frames but also to assess the confidence in these estimates is important in many applications involving motion estimation from video imagery.