Object stereo, Slide for Bleyer 10 paper

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Yichong Bai

Science

Problem
• Image pair  Disparity map + Object level segmentation
• “A combined algorithm for stereo matching and object
segmentation”
2014/3/25 Yichong Bai Object Stereo 2

Overview
• Object level
• Segmentation in object level
• Model in object level
• Pixel level
• Pixel-corresponding needed
• 3D connectivity term
• Works with occlusion
• Slow, 20m/p
2014/3/25 Yichong Bai Object Stereo 3

Difference with ours
• Object level  too much semantics
• Initial disparity map needed
• Too slow
2014/3/25 Yichong Bai Object Stereo 4

Model
• Scene Representation
• Coarse to fine
• Object = object plane + parallax
• Parallax, surface-based representation
• Object
• Color model
• Parallax model
• Object plane
2014/3/25 Yichong Bai Object Stereo 5

Model
• Problem Formulation
• F: Pixel  Planes ( Depth)
• O: Pixel  Object
•
2014/3/25 Yichong Bai Object Stereo 6

Model
• Terms
• Photo Consistency
• Pixel dissimilarity
• Occlusion
• Corresponding pixels  same depth plane and object
•
•
2014/3/25 Yichong Bai Object Stereo 7

Model
• Terms
• Object Coherence
•
2014/3/25 Yichong Bai Object Stereo 8

Model
• Terms
• Depth Plane-Coherency
•
2014/3/25 Yichong Bai Object Stereo 9

Model
• Terms
• Object-Color
• GMM
• the probability that a pixel lies inside the object according to its color value
2014/3/25 Yichong Bai Object Stereo 10

Model
• Terms
• Object-Parallax
• regularizes the disparities of an object with respect to its object plane
• parallax is likely to be compact
• non-parametric histogram
•
• is histogram probability
2014/3/25 Yichong Bai Object Stereo 11

Model
• Terms
• Object-MDL
• Small no. of objects
2014/3/25 Yichong Bai Object Stereo 12

Model
• Terms
• 3D Connectivity Prior
• Connectivity = same object OR occluded
• Approximation:
• We randomly sample a large set of pairs of points p and q, where p and q belong
to different connected components of the object. We then draw a line between
p and q and check if all pixels on the line satisfy condition (10).
2014/3/25 Yichong Bai Object Stereo 13

Solve
• Energy Minimization
• Fusion move
• Proposal generator
• Like generics algorithm
• Proposal  Fuse  Evaluate
2014/3/25 Yichong Bai Object Stereo 14

Solve
• Proposals
• Initialization
• We first compute a disparity map F using the fast stereo matcher
• F is now derived by fitting a plane to each color segment using the initial
disparity map
• To derive O, we take the color segmentation result and group segments that
have similar depths according to F
• GMM: EM
• 30 Initial proposals, with difference segmentations and parameters
2014/3/25 Yichong Bai Object Stereo 15

Solve
• Iteration
• Refit
• Fix F, refine O
• Color model, Object plane, Parallax model
• Expansion
• derived by setting all pixels of F to f and all pixels of O to o
2014/3/25 Yichong Bai Object Stereo 16

Evaluation
• Middlebury benchmark
• Works best on cone set (artificial planar scene)
2014/3/25 Yichong Bai Object Stereo 17

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Object stereo, Slide for Bleyer 10 paper

1. Object Stereo 2014/3/25 Yichong Bai Object Stereo 1

2. Problem • Image pair  Disparity map + Object level segmentation • “A combined algorithm for stereo matching and object segmentation” 2014/3/25 Yichong Bai Object Stereo 2

3. Overview • Object level • Segmentation in object level • Model in object level • Pixel level • Pixel-corresponding needed • 3D connectivity term • Works with occlusion • Slow, 20m/p 2014/3/25 Yichong Bai Object Stereo 3

4. Difference with ours • Object level  too much semantics • Initial disparity map needed • Too slow 2014/3/25 Yichong Bai Object Stereo 4

5. Model • Scene Representation • Coarse to fine • Object = object plane + parallax • Parallax, surface-based representation • Object • Color model • Parallax model • Object plane 2014/3/25 Yichong Bai Object Stereo 5

6. Model • Problem Formulation • F: Pixel  Planes ( Depth) • O: Pixel  Object • 2014/3/25 Yichong Bai Object Stereo 6

7. Model • Terms • Photo Consistency • Pixel dissimilarity • Occlusion • Corresponding pixels  same depth plane and object • • 2014/3/25 Yichong Bai Object Stereo 7

8. Model • Terms • Object Coherence • 2014/3/25 Yichong Bai Object Stereo 8

9. Model • Terms • Depth Plane-Coherency • 2014/3/25 Yichong Bai Object Stereo 9

10. Model • Terms • Object-Color • GMM • the probability that a pixel lies inside the object according to its color value 2014/3/25 Yichong Bai Object Stereo 10

11. Model • Terms • Object-Parallax • regularizes the disparities of an object with respect to its object plane • parallax is likely to be compact • non-parametric histogram • • is histogram probability 2014/3/25 Yichong Bai Object Stereo 11

12. Model • Terms • Object-MDL • Small no. of objects 2014/3/25 Yichong Bai Object Stereo 12

13. Model • Terms • 3D Connectivity Prior • Connectivity = same object OR occluded • Approximation: • We randomly sample a large set of pairs of points p and q, where p and q belong to different connected components of the object. We then draw a line between p and q and check if all pixels on the line satisfy condition (10). 2014/3/25 Yichong Bai Object Stereo 13

14. Solve • Energy Minimization • Fusion move • Proposal generator • Like generics algorithm • Proposal  Fuse  Evaluate 2014/3/25 Yichong Bai Object Stereo 14

15. Solve • Proposals • Initialization • We first compute a disparity map F using the fast stereo matcher • F is now derived by fitting a plane to each color segment using the initial disparity map • To derive O, we take the color segmentation result and group segments that have similar depths according to F • GMM: EM • 30 Initial proposals, with difference segmentations and parameters 2014/3/25 Yichong Bai Object Stereo 15

16. Solve • Iteration • Refit • Fix F, refine O • Color model, Object plane, Parallax model • Expansion • derived by setting all pixels of F to f and all pixels of O to o 2014/3/25 Yichong Bai Object Stereo 16

17. Evaluation • Middlebury benchmark • Works best on cone set (artificial planar scene) 2014/3/25 Yichong Bai Object Stereo 17

Object stereo, Slide for Bleyer 10 paper

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