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Titlebook: Stereo Scene Flow for 3D Motion Analysis; Andreas Wedel,Daniel Cremers Book 2011 Springer-Verlag London Limited 2011 3D Reconstruction.Ene

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Optical Flow Estimation,tion field is referred to as optical flow field, a two-dimensional vector field on the image plane. Because it is nearly impossible to cover the vast amount of approaches in the literature, in this chapter we set the focus on energy minimization approaches which estimate a dense flow field. The term
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Residual Images and Optical Flow Results,ous solutions to this problem are to either explicitly model the physical effect of illumination or to pre-filter the images so as to only preserve the illumination-independent information. The first approach is quite sophisticated because it involves the generation of a physical model of the observ
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Scene Flow,ensional world can be derived from stereo image sequences. The proposed algorithm takes into account image pairs from two consecutive times and computes both depth and a 3D motion vector associated with each point in the image. We particularly investigate a decoupled approach of depth estimation and
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Extensions of Scene Flow,for many driver assistance systems and an important part of machine visual kinesthesia. In this chapter we present two extensions of scene flow, making it further amenable to practical challenges of driver assistance. Firstly, we present a framework for scene-flow-based moving object detection and s
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Conclusion and Outlook,ences—from the early variational approach of Horn and Schunck for 2D optic flow estimation to recent variational approaches for 3D scene flow estimation and extensions. In particular, we discussed several algorithmic strategies for minimizing respective functionals, with particular emphasis on an al
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Appendix: Data Terms and Quadratic Optimization,m 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. .. This data term consists of a sum of one quadratic term and multiple absolute terms. The proo
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