pattern-based texture metamorphosis z. liu, c. liu, and h. shum microsoft research asia y. yu uiuc
TRANSCRIPT
Pattern-based Pattern-based Texture Texture
MetamorphosisMetamorphosis
Z. Liu, C. Liu, and H. Z. Liu, C. Liu, and H. ShumShum
Microsoft Research AsiaMicrosoft Research Asia
Y. Y. YuYuUIUC
Image Morphing vs. Image Morphing vs. Texture MorphingTexture Morphing
Specify Features and Specify Features and Correspondence *Correspondence *
Warp GenerationWarp Generation Transition ControlTransition Control
Image Morphing
* Require a lot of human intervention
Textures are usually Textures are usually homogenous with homogenous with features everywhere.features everywhere. Hard to specify featuresHard to specify features Hard to build Hard to build
correspondencecorrespondence
Image Morphing vs. Image Morphing vs. Texture MorphingTexture Morphing
Texture Morphing
Direct Blending Does Not Direct Blending Does Not WorkWork
Random Semi-structured Regular
source
target
Interesting Problems Interesting Problems In Texture MorphingIn Texture Morphing
What pair of textures?What pair of textures? Similar and repeatable patterns.Similar and repeatable patterns. Pattern distributions are alike.Pattern distributions are alike.
What is the feature?What is the feature? User define pattern.User define pattern.
How to extract so many patterns?How to extract so many patterns? Semi-automatic approach.Semi-automatic approach.
How to build correspondence?How to build correspondence? Generate a smooth warp field.Generate a smooth warp field.
Our ApproachOur Approach
1. Pattern 1. Pattern Detection and Detection and AlignmentAlignment
2. Establishing 2. Establishing Correspondence Correspondence
3. Warping and 3. Warping and BlendingBlending
Source texture Target texture
Morphing sequence
Pattern RepresentationPattern Representation
Shape DistanceShape Distance
Local Feature DistanceLocal Feature Distance
Pattern Representation & Pattern Representation & Distance MeasurementDistance Measurement
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Pattern Detection & Pattern Detection & AlignmentAlignment
Step1: Initialization by Step1: Initialization by Generalized Hough Generalized Hough Transform (GHT).Transform (GHT).
Step2: Alignment by top-Step2: Alignment by top-down verification.down verification.
Step3: Refinement by human Step3: Refinement by human intervention.intervention.
Step1: InitializationStep1: Initialization
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Pattern Detection & Pattern Detection & AlignmentAlignment
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User selected patternVoting of a pixel
Intensity image Local maximum
Original texture
(a) Independently update each (a) Independently update each landmarklandmark
(b) Update shape(b) Update shape
Iteratively do (a) and (b).Iteratively do (a) and (b).
Pattern Detection & Pattern Detection & AlignmentAlignment
Step2: AlignmentStep2: Alignment
Alignment Process
GHT initialization alignment alignment
Pattern Detection & Pattern Detection & AlignmentAlignment
Step3: RefinementStep3: Refinement
(a) False detection(a) False detection
(b) False alignment(b) False alignment
(c) More than one types of (c) More than one types of patternpattern
Correspondence by Correspondence by Minimizing Morphing PathMinimizing Morphing Path
8 56 14 21 41 36
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Warping and BlendingWarping and Blending
Forward, inverse and synthesized sequences acquiredbased on the warp field
blend
From S.Lee
More ResultsMore Results
source
target
Pattern selected
DiscussionDiscussion
About Pattern SelectionAbout Pattern Selection Can be any shapeCan be any shape User is responsibleUser is responsible
About Correspondence About Correspondence and Transition Controland Transition Control Problem of crowd patterns Problem of crowd patterns
About Warp GenerationAbout Warp Generation MFFD vs. “as rigid as possible”MFFD vs. “as rigid as possible”
Thank you !Thank you !