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Eight-Point Algorithm

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Computer Vision
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Related Concepts

Eight-Point Algorithm; Epipolar Geometry; Essential Matrix; Fundamental Matrix

Definition

The 8-point algorithm is a linear technique to estimate the essential matrix or the fundamental matrix from eight or more point correspondences.

Background

When dealing with multiple images, it is essential to determine the relative geometry between them, which is known as the epipolar geometry. Between two images of a scene, given a pair of corresponding image points \((\vec{{m}}_{i},\vec{{m}}_{i}\prime)\), the following epipolar constraint must be satisfied:

$$\widetilde{{m}}^{\prime}_{i}{^T}\mathbf{M}\widetilde{{m}}_{ i} = 0\;,$$
(1)

where \(\widetilde{\vec{{m}}}_{i} = \left [\begin{array}{*{10}c} \vec{{m}}_{i} \\ 1 \end{array} \right ]\) is point \(\vec{{m}}_{i}\) in homogeneous coordinates. Similarly, \(\widetilde{\vec{{m}}}_{i}\prime\) is point \(\vec{{m}}_{i}\prime\) in homogeneous coordinates. Matrix \(\mathbf{M}\)is a 3 ×3 matrix. If the images are calibrated with known...

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References

  1. Hartley R (1997) In defense of the eight-point algorithm. IEEE Trans Pattern Anal Mach Intell 19(6):580–593

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  2. Faugeras O, Luong QT, Papadopoulo T (2001) The geometry of multiple images. MIT, Cambridge

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  3. Hartley R, Zisserman A (2000) Multiple view geometry in computer vision. Cambridge University Press, Cambridge/New York

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  5. Zhang Z (1998) On the optimization criteria used in two-view motion analysis. IEEE Trans Pattern Anal Mach Intell 20(7):717–729

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  6. Zhang Z (1997) Motion and structure from two perspective views: from essential parameters to euclidean motion via fundamental matrix. J Opt Soc Am A 14(11): 2938–2950

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Correspondence to Zhengyou Zhang .

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© 2014 Springer Science+Business Media New York

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Zhang, Z. (2014). Eight-Point Algorithm. In: Ikeuchi, K. (eds) Computer Vision. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-31439-6_156

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