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Appendix: Data Terms and Quadratic Optimization

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Stereo Scene Flow for 3D Motion Analysis
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Abstract

In the first part of this chapter we complement Chap. 2 by giving two examples for data terms derived from the classic optical flow constraint and from an adaptive fundamental matrix constraint.

In the second part we outline the proof for the thresholding scheme used in the data term optimizing step introduced in the refinement flow estimation in Chap. 2. This data term consists of a sum of one quadratic term and multiple absolute terms. The proof uses the Karush–Kuhn–Tucker conditions for convex quadratic optimization under linear inequality constraints and is detailed for a setting with a single data term and one with two data terms.

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References

  1. Karush, W.: Minima of functions of several variables with inequalities as side constraints. Ph.D. thesis, Dept. of Mathematics, University of Chicago (1939)

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Correspondence to Andreas Wedel .

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© 2011 Springer-Verlag London Limited

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Wedel, A., Cremers, D. (2011). Appendix: Data Terms and Quadratic Optimization. In: Stereo Scene Flow for 3D Motion Analysis. Springer, London. https://doi.org/10.1007/978-0-85729-965-9_8

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  • DOI: https://doi.org/10.1007/978-0-85729-965-9_8

  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-964-2

  • Online ISBN: 978-0-85729-965-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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