Graph cut algorithms for binocular stereo with occlusions
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Graph Cut Algorithms for Binocular Stereo with Occlusions. Vladimir Kolmogorov, Ramin Zabih. Overview:. Traditional Stereo Methods Energy Minimization via Graph Cuts Stereo with Occlusions Voxel Labeling Algorithm Pixel Labeling Algorithm Results and Conclusions.

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Presentation Transcript

Overview
Overview:

  • Traditional Stereo Methods

  • Energy Minimization via Graph Cuts

  • Stereo with Occlusions

  • Voxel Labeling Algorithm

  • Pixel Labeling Algorithm

  • Results and Conclusions

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Traditional stereo methods
Traditional Stereo Methods

Traditional Stereo Problem

pixel correspondences  labeling (disparity)

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Traditional stereo methods disparity
Traditional Stereo MethodsDisparity

disparity

depth

 disparity ~ depth

ground truth disparity

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Traditional stereo methods binocular stereo
Traditional Stereo MethodsBinocular Stereo

  • goal is to compute pixels correspondences

  • traditional stereo problem  pixel labeling problem

  • advantage: can be solved by graph cuts

  • problem is formulated as energy term

  • new goal: find the minimizing labeling

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Traditional stereo methods energy function

we assign the label to pixel p when p of image I corresponds to p + in I‘

Traditional Stereo MethodsEnergy Function

find labeling that minimizes

cost for assigning labels

smoothness term

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Traditional stereo methods energy function1
Traditional Stereo Methods corresponds to p + in I‘Energy Function

  • data cost – gives penalty for different intensities

  • smoothness term – gives penalty for discontinuities (Potts model)

other models:

absolute distance

quadratic

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Energy minimization via graph cuts
Energy Minimization via Graph Cuts corresponds to p + in I‘

Max-flow / Min-Cut

(Ford and Fulkerson Algorithm, Push-Relabel Method)

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Energy minimization via graph cuts1

α corresponds to p + in I‘-expansion

α-β-swap

Initial Labeling

Energy Minimization via Graph Cuts

  • convex V vs. metric / semimetric

  • α-β-swap move

  • α-expansion move: assigning label α to an arbitrary set of pixels

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Stereo with occlusions
Stereo with Occlusions corresponds to p + in I‘

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Stereo with occlusions1
Stereo with Occlusions corresponds to p + in I‘

  • treat input symmetrically

  • scene elements only visible in single view

  • physically correct scenes  geometric constraints  occlusions  physically possible labelings

  • introduce constraints in the problem formulation

  • graph cuts perform unconstrained energy minimization

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Voxel labeling algorithm
Voxel Labeling Algorithm corresponds to p + in I‘

  • discrete scene of voxels

  • voxel v is active when visible from both cameras

  • uniqueness constraint – 1:1 correspondence of pixels

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Voxel labeling algorithm energy function
Voxel Labeling Algorithm corresponds to p + in I‘Energy Function

smoothness term

(Potts model)

matching penalty

(only active voxels)

occlusion penalty

set of occluded pixels

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Pixel labeling algorithm energy function
Pixel Labeling Algorithm corresponds to p + in I‘Energy Function

like traditional stereo but for both images e.g. Potts model

active ?

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Minimizing the energy
Minimizing the Energy corresponds to p + in I‘

  • convert constrained into unconstrained minimization problem

    • write as sum over pairs

    • form of energy function = standard stereo problem

  • minimization with α-expansion algorithm

  • modified definition of α-expansion move for voxel labeling

(0=valid, else ∞)

uniqueness

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Results and conclusions

traditional s.p. corresponds to p + in I‘

voxel labeling

pixel labeling

Results and Conclusions

ground truth

Tsukuba ref. image

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Results and conclusions1
Results and Conclusions corresponds to p + in I‘

  • efficient energy minimization polynominal time instead of exponential time

  • traditional stereo algorithm is faster

  • pixel labeling better than voxel labeling:

    • prohibits ‚holes‘ in the scene

    • allows to use other effective smoothness terms

  • algorithms can be extended for multiple cameras

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Multi view stereo via volumetric graph cuts
Multi-view Stereo via Volumetric Graph Cuts corresponds to p + in I‘

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Recent work
Recent Work corresponds to p + in I‘

Graph-cut-based stereo matching using image segmentation with symmetrical treatment of occlusions, 2006 TUW

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


Questions
Questions? corresponds to p + in I‘

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


References
References corresponds to p + in I‘

  • M. Bleyer, M. Gelautz, „Graph-cut-based stereo matching using image segmentation with symmetrical treatment of occlusions“, 2007

  • Y. Boykov, O. Veksler, R. Zabih, „Fast Approximate Energy Minimization via Graph Cuts“, 2001

  • V. Kolmogorov, R. Zabih, „Graph Cut Algorithms for Binocular Stereo with Occlusions“,2005

  • V. Kolmogorov, R. Zabih, „What energy functions can be minimized via graph cuts“, 2004

  • V. Kolmogorov, R. Zabih, „Generalized multi-camera scene reconstruction using graph cuts“, July 2003

  • V. Kolmogorov, R. Zabih, „Multi-camera Scene Reconstruction via Graph Cuts“, 2002

  • S. Seits, C. Dyer, „Photorealistic Scene Reconstruction by Voxel Coloring“, 1997

  • R.Szeliski, R. Zabih, „An Experimental Comparison of Stereo Algorithms“, 1999

Graph Cut Algorithms for Binocular Stereo with Occlusions

Math Basics for Vision and Graphis 2007


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