Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast and High Quality Overlap Fast and High Quality Overlap Repair for Patch-Based Texture Repair for Patch-Based Texture

SynthesisSynthesis

Andrew NealenAndrew NealenMarc AlexaMarc Alexa

Discrete Geometric Modeling Group (DGM)Discrete Geometric Modeling Group (DGM)Technische Universität DarmstadtTechnische Universität Darmstadt

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Our Setting: 2D Texture Synthesis

nxm Input Texture

NxM Output Texture

► The goal: Synthesize an output texture which is perceptually similar to the input texture. Also ensure that the result contains sufficient variation.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Patch-Based Texture Synthesis

Some Existing Methods

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

A B

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

A B

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

A B

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

__22

A B

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

__ ==22

overlap error

A B

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

__ ==22

overlap error

A B

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

__ ==22

overlap error

A B

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

__ ==22

overlap error

A B

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► A Very Popular 2D Texture Synthesis Method• Image Quilting [Efros and Freeman 2001]• Graphcut Texures [Kwatra et. al 2003]• Wang Tiles [Cohen et. al 2003]

Patch-Based Texture Synthesis

Some Existing Methods

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► Introduced at EGSR 2003 [Nealen and Alexa]

• Adaptive Patch Sampling, like Hierarchical Pattern Mapping [Soler et. al 2002]

• Per-Pixel Overlap Re-synthesis

Patch-Based Texture Synthesis

Hybrid Texture Synthesis (HTS)

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Hybrid Texture SynthesisMethod

Result (N x M)

Input (n x m)

Intermediate Result

Result (N x M)

Goal:From nxm, synthesize

NxM

similar, but not identical

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Result (N x M)Result (N x M)

Goal:From nxm, synthesize

NxM

similar, but not identical

Input (n x m)

Intermediate Result

Hybrid Texture SynthesisMethod

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Goal:From nxm, synthesize

NxM

similar, but not identical

Result (N x M)

Input (n x m)

Intermediate Result

Result (N x M)

Patch-Search in the Input + Copy to Result + Mark Invalid Pixels

Hybrid Texture SynthesisMethod

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Result (N x M)

Input (n x m)

Intermediate Result

Result (N x M)

Goal:From nxm, synthesize

NxM

similar, but not identical

Patch-Search in the Input + Copy to Result + Mark Invalid Pixels

Per-Pixel Re-synthesis Steps (for each Patch)

Hybrid Texture SynthesisMethod

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Result (N x M)

Input (n x m)

Intermediate Result

Result (N x M)

Goal:From nxm, synthesize

NxM

similar, but not identical

Patch-Search in the Input + Copy to Result + Mark Invalid Pixels

Per-Pixel Re-synthesis Steps (for each Patch)

Hybrid Texture SynthesisMethod

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Result (N x M)

Input (n x m)

Intermediate Result

Result (N x M)

Goal:From nxm, synthesize

NxM

similar, but not identical

Patch-Search in the Input + Copy to Result + Mark Invalid Pixels

Per-Pixel Re-synthesis Steps (for each Patch)

Hybrid Texture SynthesisMethod

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Result (N x M)

Input (n x m)

Intermediate Result

Result (N x M)

Goal:From nxm, synthesize

NxM

similar, but not identical

Patch-Search in the Input + Copy to Result + Mark Invalid Pixels

Per-Pixel Re-synthesis Steps (for each Patch)

Hybrid Texture SynthesisMethod

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Goal:From nxm, synthesize

NxM

similar, but not identical

Result (N x M)

Input (n x m)

Intermediate Result

Result (N x M)

Patch-Search in the Input + Copy to Result + Mark Invalid Pixels

Per-Pixel Re-synthesis Steps (for each Patch)

Hybrid Texture SynthesisMethod

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Hybrid Texture SynthesisGeneralization: Pro and Con

► Pro: General Method for Overlap Repair• Complementary to other Methods, such as

Minimum-Error-Boundary-Cut (MEBC) or Feathering, yet oftentimes produces better results

• Generalizes to arbitrary patch shapes, i.e. is applicable to Graphcut Textures, Wang Tiles, etc.

► Con: Computationally Expensive• Exhaustive search for each invalid pixel in the

overlap, based on mostly irregular valid neighborhood

• Has O(rN log N) complexity -> Doesn‘t scale well.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Hybrid Texture SynthesisGeneralization: Pro and Con

► Pro: General Method for Overlap Repair• Complementary to other Methods, such as

Minimum-Error-Boundary-Cut (MEBC) or Feathering, yet oftentimes produces better results

• Generalizes to arbitrary patch shapes, i.e. is applicable to Graphcut Textures, Wang Tiles, etc.

► Con: Computationally Expensive• Exhaustive search for each invalid pixel in the

overlap, based on mostly irregular valid neighborhood

• Has O(rN log N) complexity -> Doesn‘t scale well.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Hybrid Texture SynthesisGeneralization: Pro and Con

► Pro: General Method for Overlap Repair• Complementary to other Methods, such as

Minimum-Error-Boundary-Cut (MEBC) or Feathering, yet oftentimes produces better results

• Generalizes to arbitrary patch shapes, i.e. is applicable to Graphcut Textures, Wang Tiles, etc.

► Con: Computationally Expensive• Exhaustive search for each invalid pixel in the

overlap, based on mostly irregular valid neighborhood

• Has O(rN log N) complexity -> Doesn‘t scale well.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast Overlap RepairBasic Idea

► Inspiration• Ashikhmin: Synthesizing Natural Textures

[2001] termed Coherence Search• Tong et. al‘s extension: k-Coherence Search

[2002]

► Basic Idea: Intelligently Reduce Search Space• Only search within a set of coherent pixels• Introduce Trade-off between quality and speed

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

► Applying Coherence Search• For each pixel in the output, store its location in

the input in a source map (same size as the output texture)

Input Texture

Intermediate Result + Source Map

Fast Overlap Repair Coherence Search

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast Overlap Repair Coherence Search

► Applying Coherence Search• When searching for a new pixel, only consider

input pixels which are coherent with neighboring output pixels

Input Texture

Source Map Lookup

Intermediate Result + Source Map

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast Overlap Repair Coherence Search

► Applying Coherence Search• When searching for a new pixel, only consider

input pixels which are coherent with neighboring output pixels

Input Texture

Intermediate Result + Source Map

Source Map Lookup

Consequence in this example: Only two possible candidates

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast Overlap Repair Coherence Search

► Applying Coherence Search• Simply comparing to the coherent pixels results in

seams similar to Image Quilting (MEBC)

Example:

64x64 Texture Synthesized from four 32x32 Patches Coherence Exhaustive

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast Overlap Repair Coherence Search

► Applying Coherence Search• Simply comparing to the coherent pixels results in

seams similar to Image Quilting (MEBC)

Example:

64x64 Texture Synthesized from four 32x32 Patches Coherence Exhaustive

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast Overlap Repair Coherence Search

► Applying Coherence Search• Simply comparing to the coherent pixels results in

seams similar to Image Quilting (MEBC)

Example:

64x64 Texture Synthesized from four 32x32 Patches Coherence Exhaustive

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast Overlap Repair k-Coherence Search

Input Texture

Intermediate Result + Source Map

Source Map Lookup

► Better: Applying k-Coherence Search

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast Overlap Repair k-Coherence Search

► Better: Applying k-Coherence Search• Extend the set by the k-nearest neighbors (knn) of

each coherent pixel (in feature space) and remove duplicates

Intermediate Result + Source Map

Source Map Lookup

Input Texture

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast Overlap Repair k-Coherence Search

► Precomputation of knn Data Structure• Performed once for each nxm input texture and

stored for repeated use

• User defines size of box-shaped neighborhood np

• For each of the nxm input pixels─ Construct feature vector by ordered concatenation of the npx np

RGB-triples in the box-shaped neighborhood

• Dimension reduction (75-90%) by applying PCA• Compute indices of k-nearest neighbors to each

pixel

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Fast Overlap Repair k-Coherence Search

► Source Map Maintenance• Each valid pixel in the overlap region is a linear

blend (feathering) of at least two original pixel values, i.e. from at least two different sources

• To avoid the maintenance of multiple source maps, simply store the source of the pixel with greatest contribution in a single source map

Blue: invalid overlap pixels

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results varying k

k = 1

k = 11

k = 4

Exhaustive

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results varying k

k = 1

k = 11

k = 4

Exhaustive

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results varying k

k = 1

k = 11

k = 4

Exhaustive

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results varying k

k = 1

k = 11

k = 4

Exhaustive

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results timings

InputExhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

scales 64×64 δmax = 0.02 Δmax = 0.05

rock 128×128 δmax = 0.02 Δmax = 0.05

stonewall 200×200

δmax = 0.02 Δmax = 0.03

Pre: 0 sec.

Synth: 283 sec.

Pre: 0 sec.

Synth: 533 sec.

Pre: 0 sec.

Synth: 985 sec.

Pre: 6+3 sec.

Synth: 226 sec.

Pre: 45+62 sec.

Synth: 226 sec.

Pre: 247+28 s

Synth: 178 sec.

Pre: 6+4 sec.

Synth: 427 sec.

Pre: 45+74 sec.

Synth: 415 sec.

Pre: 247+37 s

Synth: 350 sec.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results timings

InputExhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

scales 64×64 δmax = 0.02 Δmax = 0.05

rock 128×128 δmax = 0.02 Δmax = 0.05

stonewall 200×200

δmax = 0.02 Δmax = 0.03

Pre: 0 sec.

Synth: 283 sec.

Pre: 0 sec.

Synth: 533 sec.

Pre: 0 sec.

Synth: 985 sec.

Pre: 6+3 sec.

Synth: 226 sec.

Pre: 45+62 sec.

Synth: 226 sec.

Pre: 247+28 s

Synth: 178 sec.

Pre: 6+4 sec.

Synth: 427 sec.

Pre: 45+74 sec.

Synth: 415 sec.

Pre: 247+37 s

Synth: 350 sec.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results timings

InputExhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

scales 64×64 δmax = 0.02 Δmax = 0.05

rock 128×128 δmax = 0.02 Δmax = 0.05

stonewall 200×200

δmax = 0.02 Δmax = 0.03

Pre: 0 sec.

Synth: 283 sec.

Pre: 0 sec.

Synth: 533 sec.

Pre: 0 sec.

Synth: 985 sec.

Pre: 6+3 sec.

Synth: 226 sec.

Pre: 45+62 sec.

Synth: 226 sec.

Pre: 247+28 s

Synth: 178 sec.

Pre: 6+4 sec.

Synth: 427 sec.

Pre: 45+74 sec.

Synth: 415 sec.

Pre: 247+37 s

Synth: 350 sec.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results timings

InputExhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

scales 64×64 δmax = 0.02 Δmax = 0.05

rock 128×128 δmax = 0.02 Δmax = 0.05

stonewall 200×200

δmax = 0.02 Δmax = 0.03

Pre: 0 sec.

Synth: 283 sec.

Pre: 0 sec.

Synth: 533 sec.

Pre: 0 sec.

Synth: 985 sec.

Pre: 6+3 sec.

Synth: 226 sec.

Pre: 45+62 sec.

Synth: 226 sec.

Pre: 247+28 s

Synth: 178 sec.

Pre: 6+4 sec.

Synth: 427 sec.

Pre: 45+74 sec.

Synth: 415 sec.

Pre: 247+37 s

Synth: 350 sec.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results timings

InputExhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

scales 64×64 δmax = 0.02 Δmax = 0.05

rock 128×128 δmax = 0.02 Δmax = 0.05

stonewall 200×200

δmax = 0.02 Δmax = 0.03

Pre: 0 sec.

Synth: 283 sec.

Pre: 0 sec.

Synth: 533 sec.

Pre: 0 sec.

Synth: 985 sec.

Pre: 6+3 sec.

Synth: 226 sec.

Pre: 45+62 sec.

Synth: 226 sec.

Pre: 247+28 s

Synth: 178 sec.

Pre: 6+4 sec.

Synth: 427 sec.

Pre: 45+74 sec.

Synth: 415 sec.

Pre: 247+37 s

Synth: 350 sec.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results timings

InputExhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

scales 64×64 δmax = 0.02 Δmax = 0.05

rock 128×128 δmax = 0.02 Δmax = 0.05

stonewall 200×200

δmax = 0.02 Δmax = 0.03

Pre: 0 sec.

Synth: 283 sec.

Pre: 0 sec.

Synth: 533 sec.

Pre: 0 sec.

Synth: 985 sec.

Pre: 6+3 sec.

Synth: 226 sec.

Pre: 45+62 sec.

Synth: 226 sec.

Pre: 247+28 s

Synth: 178 sec.

Pre: 6+4 sec.

Synth: 427 sec.

Pre: 45+74 sec.

Synth: 415 sec.

Pre: 247+37 s

Synth: 350 sec.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results timings

InputExhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

scales 64×64 δmax = 0.02 Δmax = 0.05

rock 128×128 δmax = 0.02 Δmax = 0.05

stonewall 200×200

δmax = 0.02 Δmax = 0.03

Pre: 0 sec.

Synth: 283 sec.

Pre: 0 sec.

Synth: 533 sec.

Pre: 0 sec.

Synth: 985 sec.

Pre: 6+3 sec.

Synth: 226 sec.

Pre: 45+62 sec.

Synth: 226 sec.

Pre: 247+28 s

Synth: 178 sec.

Pre: 6+4 sec.

Synth: 427 sec.

Pre: 45+74 sec.

Synth: 415 sec.

Pre: 247+37 s

Synth: 350 sec.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results timings

InputExhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

scales 64×64 δmax = 0.02 Δmax = 0.05

rock 128×128 δmax = 0.02 Δmax = 0.05

stonewall 200×200

δmax = 0.02 Δmax = 0.03

Pre: 0 sec.

Synth: 283 sec.

Pre: 0 sec.

Synth: 533 sec.

Pre: 0 sec.

Synth: 985 sec.

Pre: 6+3 sec.

Synth: 226 sec.

Pre: 45+62 sec.

Synth: 226 sec.

Pre: 247+28 s

Synth: 178 sec.

Pre: 6+4 sec.

Synth: 427 sec.

Pre: 45+74 sec.

Synth: 415 sec.

Pre: 247+37 s

Synth: 350 sec.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results timings

InputExhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

scales 64×64 δmax = 0.02 Δmax = 0.05

rock 128×128 δmax = 0.02 Δmax = 0.05

stonewall 200×200

δmax = 0.02 Δmax = 0.03

Pre: 0 sec.

Synth: 283 sec.

Pre: 0 sec.

Synth: 533 sec.

Pre: 0 sec.

Synth: 985 sec.

Pre: 6+3 sec.

Synth: 226 sec.

Pre: 45+62 sec.

Synth: 226 sec.

Pre: 247+28 s

Synth: 178 sec.

Pre: 6+4 sec.

Synth: 427 sec.

Pre: 45+74 sec.

Synth: 415 sec.

Pre: 247+37 s

Synth: 350 sec.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results timings

InputExhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

scales 64×64 δmax = 0.02 Δmax = 0.05

rock 128×128 δmax = 0.02 Δmax = 0.05

stonewall 200×200

δmax = 0.02 Δmax = 0.03

Pre: 0 sec.

Synth: 283 sec.

Pre: 0 sec.

Synth: 533 sec.

Pre: 0 sec.

Synth: 985 sec.

Pre: 6+3 sec.

Synth: 226 sec.

Pre: 45+62 sec.

Synth: 226 sec.

Pre: 247+28 s

Synth: 178 sec.

Pre: 6+4 sec.

Synth: 427 sec.

Pre: 45+74 sec.

Synth: 415 sec.

Pre: 247+37 s

Synth: 350 sec.

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results

Exhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Results

Exhaustive

n = 7x7

k-Coherence

n = 3x3 | k = 5

k-Coherence

n = 5x5 | k = 11

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

ResultsSynthesis Comparisons

Input

Efros/Leung Wei/Levoy

IQ PBS HTS

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

ResultsSynthesis Comparisons

Input

Efros/Leung Wei/Levoy

IQ PBS HTS

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

ResultsSynthesis Comparisons

Input

Efros/Leung Wei/Levoy

IQ PBS HTS

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

ResultsSynthesis Comparisons

Input

Efros/Leung Wei/Levoy

IQ PBS HTS

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

ResultsSynthesis Comparisons

Input

Efros/Leung Wei/Levoy

IQ PBS HTS

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

ResultsSynthesis Comparisons

Input

Efros/Leung Wei/Levoy

IQ PBS HTS

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

ResultsSynthesis Comparisons

Input

Efros/Leung Wei/Levoy

IQ PBS HTS

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Conclusions and Future Work

► Improve Error Metric• Still using the L2 norm due to its simplicity

• Develop a metric which takes feature mismatch into account

• Texton map approach [Zhang et al. 2003]• Feature Map [Wu and Yu 2004] performs even

better, and for near-regular textures, see [Liu et. al 2004] (both to appear at SIGGRAPH 2004)

Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004

Questions ?

► Contact Information

Andrew Nealennealen@informatik.tu-darmstadt.de

Marc Alexaalexa@informatik.tu-darmstadt.de

http://www.dgm.informatik.tu-darmstadt.de

Matlab code:http://www.dgm.informatik.tu-darmstadt.de/research/texsynth.html