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Primal Sketch Integrating Structure and TexturePowerPoint Presentation

Primal Sketch Integrating Structure and Texture

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Primal Sketch Integrating Structure and Texture

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Integrating Structure and Texture

Ying Nian Wu

UCLA Department of Statistics

Keck Meeting

April 28, 2006

Guo, Zhu, Wu (ICCV, 2003; GMBV, 2004; CVIU, 2006)

A Generative Model for Natural Images

texture regions

input image

sketch graph

+

=

synthesized image

sketchable image

synthesized textures

Olshausen and Field (1996)

Markov Property:

MRF model = Gibbs distribution

Besag (1974)

Geman and Geman (1984)

Cross and Jain (1983)

One example of neighborhood

Feature statistics: histograms of filter responses

(Heeger and Bergen, 1995)

Filtering – convolution

original image I

filter responses J

of the “dy” filter

a set of filters F

Sparse Coding models target low complexity patterns.

const: related to the dictionary

MRF models target high complexity patterns.

p*: fitted MRF

q: any distribution

Image pixels = Sketchable & Non-sketchable

Sketchable: sparse coding using image primitives

Non-sketchable: feature statistics/Markov random fields

- Integration:
- Non-sketchable interpolates sketchable
- Non-sketchable recycles failed sketch detections

Elder and Zucker, 1998

Alignment across spatial and frequency domains

Integrating structure and texture

Sketch Graph

Sketches

Alignment

Gabor filters

Non-alignment

Textures

Pool marginal histograms

First: Sketch pursuit aided by Gabors

Second: Non-sketchable texturing

Sketchability test

Approximated model

input image

edge/ridge strength

Edge/ridge map

Proposals: a set of sketches as candidates.

Select the sketches in the order of likelihood gain.

Sketch Pursuit Phase IIRefinement

Refinement

Initialization

Evolve the sketch graph by graph operators.

- Randomly choose a local sub-graph (S0)
- Try all 10 pair of graph operators 1~ 5 steps, to generate a set of new graph candidates (S4,S2,S3)
- Compare all new graph candidates
- Select the one with the largest posterior gain (e.g. S4), accept the new graph. If no positive gain, no update.
- Repeat 1~4 until no update

S0

G1

G3

S1

S2

S3

G4

S4

codes for the vertices:

152*2*9 = 2,736 bits

codes for the strokes:

275*2*4.7 = 2, 585 bits

sketch graph

codes for the profiles:

275*(2.4*8+1.4*2) = 6,050 bits

Total codes for structures (18,185 pixels)

11,371 bits = 1,421 bytes

sketchable image

codes for the region boundaries:

3659*3 = 10,977 bits

texture regions

codes for the texture histograms:

7*5*13*4.5 =2,048 bits

Total codes for textures (41,815 pixels)

13,025 bits = 1,628 bytes

Total codes for whole image

(72,000 pixels), 3,049 bytes

synthesized textures

Wu, Zhu, Bahrami, Li (2006)