Fast and High Quality Overlap Repair for Patch-Based Texture Synthesis Andrew Nealen Marc Alexa Discrete Geometric Modeling Group (DGM) Technische Universität Darmstadt Andrew Nealen and Marc.
Download ReportTranscript Fast and High Quality Overlap Repair for Patch-Based Texture Synthesis Andrew Nealen Marc Alexa Discrete Geometric Modeling Group (DGM) Technische Universität Darmstadt Andrew Nealen and Marc.
Fast and High Quality Overlap Repair for Patch-Based Texture Synthesis
Andrew Nealen Marc Alexa
Discrete Geometric Modeling Group (DGM) Technische Universität Darmstadt Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Our Setting: 2D Texture Synthesis
n x m Input Texture N x M 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
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
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]
A B
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]
A B
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]
A B
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]
A B
_ 2 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]
A B
_ 2
= overlap error
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]
A B
_ 2
= overlap error
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]
A B
_ 2
= overlap error
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]
A B
_ 2
= overlap error
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
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
Patch-Based Texture Synthesis
Hybrid Texture Synthesis (HTS)
►
Introduced at EGSR 2003 [Nealen and Alexa]
• Adaptive Patch Sampling, like Mapping [Soler et. al 2002] Hierarchical Pattern • Per-Pixel Overlap Re-synthesis Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Hybrid Texture Synthesis
Method Input (n x m) Intermediate Result Goal: From nxm, synthesize NxM similar, but not identical
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Hybrid Texture Synthesis
Method Input (n x m) Intermediate Result Goal: From nxm, synthesize NxM similar, but not identical
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Hybrid Texture Synthesis
Method Patch-Search in the Input + Copy to Result + Mark Invalid Pixels Input (n x m) Intermediate Result Goal: From nxm, synthesize NxM similar, but not identical
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Hybrid Texture Synthesis
Method Patch-Search in the Input + Copy to Result + Mark Invalid Pixels Input (n x m) Intermediate Result Goal: From nxm, synthesize NxM similar, but not identical Per-Pixel Re-synthesis Steps (for each Patch)
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Hybrid Texture Synthesis
Method Patch-Search in the Input + Copy to Result + Mark Invalid Pixels Input (n x m) Intermediate Result Goal: From nxm, synthesize NxM similar, but not identical Per-Pixel Re-synthesis Steps (for each Patch)
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Hybrid Texture Synthesis
Method Patch-Search in the Input + Copy to Result + Mark Invalid Pixels Input (n x m) Intermediate Result Goal: From nxm, synthesize NxM similar, but not identical Per-Pixel Re-synthesis Steps (for each Patch)
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Hybrid Texture Synthesis
Method Patch-Search in the Input + Copy to Result + Mark Invalid Pixels Input (n x m) Intermediate Result Goal: From nxm, synthesize NxM similar, but not identical Per-Pixel Re-synthesis Steps (for each Patch)
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Hybrid Texture Synthesis
Method Patch-Search in the Input + Copy to Result + Mark Invalid Pixels Input (n x m) Intermediate Result Goal: From nxm, synthesize NxM similar, but not identical Per-Pixel Re-synthesis Steps (for each Patch)
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Hybrid Texture Synthesis
Generalization: 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 based on mostly irregular invalid valid pixel in the overlap, 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 Synthesis
Generalization: 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 based on mostly irregular invalid valid pixel in the overlap, 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 Synthesis
Generalization: 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 based on mostly irregular invalid valid pixel in the overlap, 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 Repair
Basic 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
Fast Overlap Repair
Coherence Search
►
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
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
Source Map Lookup Input Texture 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
Source Map Lookup Input Texture Intermediate Result + Source Map 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
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Exhaustive
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
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Exhaustive
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
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Exhaustive
Fast Overlap Repair
k-Coherence Search
►
Better: Applying k-Coherence Search Source Map Lookup Input Texture Intermediate Result + Source Map
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
Source Map Lookup Input Texture Intermediate Result + Source Map
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 n
p
For each of the nxm input pixels • • ─ Construct feature vector by ordered concatenation of the
n p
x
n p
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 = 4 k = 1 k = 11
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Exhaustive
Results
varying k k = 4 k = 1 k = 11
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Exhaustive
Results
varying k k = 4 k = 1 k = 11
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Exhaustive
Results
varying k k = 4 k = 1 k = 11
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Exhaustive
Results
timings Input Exhaustive n = 7x7 k-Coherence n = 3x3 | k = 5 k-Coherence n = 5x5 | k = 11 scales 64 × 64 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 283 sec.
Pre: 6+3 sec.
Synth: 226 sec.
Pre: 6+4 sec.
Synth: 427 sec.
rock 128 × 128 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 533 sec.
stonewall 200 × 200 δ max Δ max = 0.02 = 0.03
Pre: 0 sec.
Synth: 985 sec.
Pre: 45+62 sec.
Synth: 226 sec.
Pre: 45+74 sec.
Synth: 415 sec.
Pre: 247+28 s Synth: 178 sec.
Pre: 247+37 s Synth: 350 sec.
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Results
timings Input Exhaustive n = 7x7 k-Coherence n = 3x3 | k = 5 k-Coherence n = 5x5 | k = 11 scales 64 × 64 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 283 sec.
Pre: 6+3 sec.
Synth: 226 sec.
Pre: 6+4 sec.
Synth: 427 sec.
rock 128 × 128 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 533 sec.
stonewall 200 × 200 δ max Δ max = 0.02 = 0.03
Pre: 0 sec.
Synth: 985 sec.
Pre: 45+62 sec.
Synth: 226 sec.
Pre: 45+74 sec.
Synth: 415 sec.
Pre: 247+28 s Synth: 178 sec.
Pre: 247+37 s Synth: 350 sec.
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Results
timings Input Exhaustive n = 7x7 k-Coherence n = 3x3 | k = 5 k-Coherence n = 5x5 | k = 11 scales 64 × 64 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 283 sec.
Pre: 6+3 sec.
Synth: 226 sec.
Pre: 6+4 sec.
Synth: 427 sec.
rock 128 × 128 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 533 sec.
stonewall 200 × 200 δ max Δ max = 0.02 = 0.03
Pre: 0 sec.
Synth: 985 sec.
Pre: 45+62 sec.
Synth: 226 sec.
Pre: 45+74 sec.
Synth: 415 sec.
Pre: 247+28 s Synth: 178 sec.
Pre: 247+37 s Synth: 350 sec.
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Results
timings Input Exhaustive n = 7x7 k-Coherence n = 3x3 | k = 5 k-Coherence n = 5x5 | k = 11 scales 64 × 64 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 283 sec.
Pre: 6+3 sec.
Synth: 226 sec.
Pre: 6+4 sec.
Synth: 427 sec.
rock 128 × 128 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 533 sec.
stonewall 200 × 200 δ max Δ max = 0.02 = 0.03
Pre: 0 sec.
Synth: 985 sec.
Pre: 45+62 sec.
Synth: 226 sec.
Pre: 45+74 sec.
Synth: 415 sec.
Pre: 247+28 s Synth: 178 sec.
Pre: 247+37 s Synth: 350 sec.
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Results
timings Input Exhaustive n = 7x7 k-Coherence n = 3x3 | k = 5 k-Coherence n = 5x5 | k = 11 scales 64 × 64 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 283 sec.
Pre: 6+3 sec.
Synth: 226 sec.
Pre: 6+4 sec.
Synth: 427 sec.
rock 128 × 128 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 533 sec.
stonewall 200 × 200 δ max Δ max = 0.02 = 0.03
Pre: 0 sec.
Synth: 985 sec.
Pre: 45+62 sec.
Synth: 226 sec.
Pre: 45+74 sec.
Synth: 415 sec.
Pre: 247+28 s Synth: 178 sec.
Pre: 247+37 s Synth: 350 sec.
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Results
timings Input Exhaustive n = 7x7 k-Coherence n = 3x3 | k = 5 k-Coherence n = 5x5 | k = 11 scales 64 × 64 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 283 sec.
Pre: 6+3 sec.
Synth: 226 sec.
Pre: 6+4 sec.
Synth: 427 sec.
rock 128 × 128 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 533 sec.
stonewall 200 × 200 δ max Δ max = 0.02 = 0.03
Pre: 0 sec.
Synth: 985 sec.
Pre: 45+62 sec.
Synth: 226 sec.
Pre: 45+74 sec.
Synth: 415 sec.
Pre: 247+28 s Synth: 178 sec.
Pre: 247+37 s Synth: 350 sec.
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Results
timings Input Exhaustive n = 7x7 k-Coherence n = 3x3 | k = 5 k-Coherence n = 5x5 | k = 11 scales 64 × 64 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 283 sec.
Pre: 6+3 sec.
Synth: 226 sec.
Pre: 6+4 sec.
Synth: 427 sec.
rock 128 × 128 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 533 sec.
stonewall 200 × 200 δ max Δ max = 0.02 = 0.03
Pre: 0 sec.
Synth: 985 sec.
Pre: 45+62 sec.
Synth: 226 sec.
Pre: 45+74 sec.
Synth: 415 sec.
Pre: 247+28 s Synth: 178 sec.
Pre: 247+37 s Synth: 350 sec.
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Results
timings Input Exhaustive n = 7x7 k-Coherence n = 3x3 | k = 5 k-Coherence n = 5x5 | k = 11 scales 64 × 64 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 283 sec.
Pre: 6+3 sec.
Synth: 226 sec.
Pre: 6+4 sec.
Synth: 427 sec.
rock 128 × 128 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 533 sec.
stonewall 200 × 200 δ max Δ max = 0.02 = 0.03
Pre: 0 sec.
Synth: 985 sec.
Pre: 45+62 sec.
Synth: 226 sec.
Pre: 45+74 sec.
Synth: 415 sec.
Pre: 247+28 s Synth: 178 sec.
Pre: 247+37 s Synth: 350 sec.
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Results
timings Input Exhaustive n = 7x7 k-Coherence n = 3x3 | k = 5 k-Coherence n = 5x5 | k = 11 scales 64 × 64 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 283 sec.
Pre: 6+3 sec.
Synth: 226 sec.
Pre: 6+4 sec.
Synth: 427 sec.
rock 128 × 128 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 533 sec.
stonewall 200 × 200 δ max Δ max = 0.02 = 0.03
Pre: 0 sec.
Synth: 985 sec.
Pre: 45+62 sec.
Synth: 226 sec.
Pre: 45+74 sec.
Synth: 415 sec.
Pre: 247+28 s Synth: 178 sec.
Pre: 247+37 s Synth: 350 sec.
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
Results
timings Input Exhaustive n = 7x7 k-Coherence n = 3x3 | k = 5 k-Coherence n = 5x5 | k = 11 scales 64 × 64 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 283 sec.
Pre: 6+3 sec.
Synth: 226 sec.
Pre: 6+4 sec.
Synth: 427 sec.
rock 128 × 128 δ max Δ max = 0.02 = 0.05
Pre: 0 sec.
Synth: 533 sec.
stonewall 200 × 200 δ max Δ max = 0.02 = 0.03
Pre: 0 sec.
Synth: 985 sec.
Pre: 45+62 sec.
Synth: 226 sec.
Pre: 45+74 sec.
Synth: 415 sec.
Pre: 247+28 s Synth: 178 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
Results
Synthesis Comparisons Input Efros/Leung Wei/Levoy IQ PBS
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
HTS
Results
Synthesis Comparisons Input Efros/Leung Wei/Levoy IQ PBS
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
HTS
Results
Synthesis Comparisons Input Efros/Leung Wei/Levoy IQ PBS
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
HTS
Results
Synthesis Comparisons Input Efros/Leung Wei/Levoy IQ PBS
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
HTS
Results
Synthesis Comparisons Input Efros/Leung Wei/Levoy IQ PBS
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
HTS
Results
Synthesis Comparisons Input Efros/Leung Wei/Levoy IQ PBS
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
HTS
Results
Synthesis Comparisons Input Efros/Leung Wei/Levoy IQ PBS
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004
HTS
Conclusions and Future Work
►
Improve Error Metric
• • Still using the L 2 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 Nealen [email protected]
Marc Alexa [email protected]
http://www.dgm.informatik.tu-darmstadt.de
Matlab code: http://www.dgm.informatik.tu-darmstadt.de/research/texsynth.html
Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004