Image Quilting for Texture Synthesis and Transfer

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Image Quilting for Texture Synthesis and Transfer

Image Quilting for TextureSynthesis and Transfer


The GoalTexture Synthesis


The GoalTexture Transfer


The Approach (Synthesis)


The Approach (Synthesis)


The Approach (Synthesis)Similarity = [f(B i ) – g(B j )] 2“Get right overlap”“Get left overlap”


The Approach (Synthesis)


The Approach (Synthesis)Notice the blocky looking boundaries


The Approach (Synthesis)Boundary optimization


e = [f(B 1 ) – g(B 2 )] 2


E ij = e ij + min(E i-1, j-1 , E i-1, j , E i-1, j+1 )Dynamic programming: E ij is the min path to that position


e 01 e 02 e 03E 12 = e 12 + min(E 01 , E 02 , E 03 )= e 12 + min(e 01 , e 02 , e 03 )


The Approach (Transfer)


The Approach (Transfer)Correspondence Map


The Approach (Transfer)(1-α) × (C i – C j ) 2α × [f(B i ) – g(B j )] 2


The Approach (Transfer)


Image Analogies


The Idea: :,?Courtesy A. Hertzmann


But how?: :,Relate these…… to these


Approximate Best MatchA A’Need to locate best pixel (p) in A’ given qqqB B’


Approximate Best Match++++++A A’Precompute an acceleration datastructure for ‘features’ in A, A’qqB B’


Approximate Best Match++++++A A’QueryqqB B’


Approximate Best MatchLookupppA A’++++++QueryqqB B’


Approximate Best MatchLookupppA A’++++++QueryqqB B’


Approximate Best MatchLookupppA A’++++++QueryqqB B’B’


Exploiting Coherence


N(q)q


p = s(q)


Consider this feature…


Approximate MatchCoherent Match


What about the features?YIQ


Shameless copying of results…Van GoghWatercolor


Van GoghWatercolor


Texture SynthesisWhich one do you think is ‘better’?


Texture Transfer

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