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Creating images the 2-D way Jean-François Lalonde April 20, 2010
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Creating images (3-D)
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Creating images (2-D + 3-D)
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Inserting objects into images
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Inserting objects into images(2-D + 3-D) [Debevec, 98]
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Inserting objects in images Realistic renderings Expensive and impractical Highly detailed geometry Highly detailed materials Very expensive [Debevec, 98]
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Alternative: Clip art Easy, intuitive, cheap Not realistic
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Creating images (2-D) Photo-realisticCartoon Expensive and impracticalCheap and intuitive Image-based renderingClip ArtPhoto Clip Art ? ?
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Photoshop-ing Composite by David Dewey
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Inserting objects into images
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Challenges object orientation scene illumination Insert THIS object: impossible!
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The use of data Insert SOME object: much easier!
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The Google model Database Sort the objects QueryResults
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2-D image vs 3-D scene
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Outline Phase I: Database annotation Phase II: Object insertion Name: person Subgroup: person, standing Height: 1.5m Local context: in shadow Illumination: sunny, bright day, no cloud Segmentation quality: excellent, >40 points Upsampling blur: low
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Data source: LabelMe Online (http://labelme.csail.mit.edu), user- contributedhttp://labelme.csail.mit.edu 170,000 objects in 40,000 images Polygons and names [Russell et al., 2005]
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Data organization Top-level categories (chosen manually, 16 total) Second-level categories (from annotations or clustering)
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Annotating the objects
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Camera parameters Assume flat ground plane all objects on ground camera roll is negligible (consider pitch only) Camera parameters: height and orientation
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Human height distribution 1.7 +/- 0.085 m (National Center for Health Statistics) Car height distribution 1.5 +/- 0.19 m (automatically learned) Camera parameters
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Object heights Database image Pixel heightsReal heights
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ObjectEstimated average height (m) Car1.51 Man1.80 Woman1.67 Parking meter1.36 Fire hydrant0.87 Estimated object heights 1.0 m Car 0.5 m ManWoman Parking meter Fire hydrant 1.5 m
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Geometry is not enough
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Illumination context Database image Environment map rough approximation Exact environment map is impossible Approximations [Khan et al., 06]
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Illumination context Database imageP(pixel|class)CIE L*a*b* histograms Automatic Photo Popup Hoiem et al., SIGGRAPH 05 Automatic Photo Popup Hoiem et al., SIGGRAPH 05
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Illumination nearest-neighbors
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Other criteria: local context
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Other criteria: segmentation LabelMe contributors not always reliable Segmentation quality 38 points / polygon4 points / polygon
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Other criteria: blur Resolution: avoid up-sampling x3 up-sampling
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Recap Phase I: Database annotation Phase II: Object insertion 3-D heightSegmentationBlur Object properties (used for sorting the database) LabelIllumination contextClusterLocal contextCamera
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Lets insert an object! Poor user-provided segmentations Noticeable seams
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Seams InputDestination image Result Visible seam! [Perez et al., 2003]
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Poisson blending: idea InputDestination Result Enforce boundary color (seamless result) Enforce same gradient than input
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Why gradients? 1-D example Regular blending bright dark
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1-D example Blending derivatives Original signalsDerivatives Reintegration results
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1-D example Gradient domainIntensity domain ?
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2-D: not so easy +1 +2 -3 4 02 5 -2 Non integrable: sum over a loop 0 Actually happens all the time in practice
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2-D: some notation Finite differences
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2-D: a (possible) solution Least-squares solution:?
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Solution: Poisson equation Popular because: Solution is obtained by solving a linear system of equations Can be solved (somewhat) efficiently \ in matlab FFT Multi-grid solvers (approximate, but really fast!) 2-D: a (popular) solution
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Results & limitations Image editing Some limitations Images need to be very well aligned Differences in background bleed through Images from [Perez et al., 2003]
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Poisson blending: improvements Drag-and-Drop Pasting [Jia et al., 2006] User-selected boundary Poisson blending Refined boundary Poisson blending Images from [Jia et al., 2006] Color bleeding
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Still not right! Not so sensitive to shadow direction [Cavanagh, 2005]
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Shadow transfer ++ == Database imageShadow estimateRefined shadow Object aloneShadow aloneObject with shadow
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User interface
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Street accident
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Bridge
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Painting
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Alley
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Failure cases Shadow transfer Porous objects
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Failure cases Best matching objects
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Pros & cons ProsCons 3-D More control (camera, geometry, lighting...) Complex! 2-D + 3-DRealistic Complex! Need access to scene 2-D (photoshop) Realistic Complex! Need to sort through images 2-D (automatic) Easy, intuitiveGeneric objects
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Thanks! jlalonde@cs.cmu.edu
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