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Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Fast and High Quality Overlap Repair for Patch-Based Texture Synthesis.

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Presentation on theme: "Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Fast and High Quality Overlap Repair for Patch-Based Texture Synthesis."— Presentation transcript:

1 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Fast and High Quality Overlap Repair for Patch-Based Texture Synthesis Andrew Nealen Marc Alexa Discrete Geometric Modeling Group (DGM) Technische Universität Darmstadt

2 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.

3 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]

4 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

5 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

6 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

7 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

8 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 _ 2 A B

9 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 _ = 2 overlap error A B

10 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 _ = 2 overlap error A B

11 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 _ = 2 overlap error A B

12 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 _ = 2 overlap error A B

13 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

14 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

15 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)

16 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Hybrid Texture Synthesis Method Result (N x M) Input (n x m) Intermediate Result Result (N x M) Goal: From nxm, synthesize NxM similar, but not identical

17 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Result (N x M) Goal: From nxm, synthesize NxM similar, but not identical Input (n x m) Intermediate Result Hybrid Texture Synthesis Method

18 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 Synthesis Method

19 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 Synthesis Method

20 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 Synthesis Method

21 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 Synthesis Method

22 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 Synthesis Method

23 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 Synthesis Method

24 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 invalid pixel in the overlap, based on mostly irregular valid neighborhood Has O(rN log N) complexity -> Doesnt scale well.

25 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 invalid pixel in the overlap, based on mostly irregular valid neighborhood Has O(rN log N) complexity -> Doesnt scale well.

26 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 invalid pixel in the overlap, based on mostly irregular valid neighborhood Has O(rN log N) complexity -> Doesnt scale well.

27 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. als 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

28 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

29 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

30 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

31 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 CoherenceExhaustive

32 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 CoherenceExhaustive

33 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 CoherenceExhaustive

34 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

35 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

36 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

37 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

38 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results varying k k = 1 k = 11 k = 4 Exhaustive

39 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results varying k k = 1 k = 11 k = 4 Exhaustive

40 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results varying k k = 1 k = 11 k = 4 Exhaustive

41 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results varying k k = 1 k = 11 k = 4 Exhaustive

42 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 = 0.02 Δ max = 0.05 rock 128×128 δ max = 0.02 Δ max = 0.05 stonewall 200×200 δ max = 0.02 Δ max = 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: sec. Synth: 226 sec. Pre: s Synth: 178 sec. Pre: 6+4 sec. Synth: 427 sec. Pre: sec. Synth: 415 sec. Pre: s Synth: 350 sec.

43 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 = 0.02 Δ max = 0.05 rock 128×128 δ max = 0.02 Δ max = 0.05 stonewall 200×200 δ max = 0.02 Δ max = 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: sec. Synth: 226 sec. Pre: s Synth: 178 sec. Pre: 6+4 sec. Synth: 427 sec. Pre: sec. Synth: 415 sec. Pre: s Synth: 350 sec.

44 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 = 0.02 Δ max = 0.05 rock 128×128 δ max = 0.02 Δ max = 0.05 stonewall 200×200 δ max = 0.02 Δ max = 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: sec. Synth: 226 sec. Pre: s Synth: 178 sec. Pre: 6+4 sec. Synth: 427 sec. Pre: sec. Synth: 415 sec. Pre: s Synth: 350 sec.

45 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 = 0.02 Δ max = 0.05 rock 128×128 δ max = 0.02 Δ max = 0.05 stonewall 200×200 δ max = 0.02 Δ max = 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: sec. Synth: 226 sec. Pre: s Synth: 178 sec. Pre: 6+4 sec. Synth: 427 sec. Pre: sec. Synth: 415 sec. Pre: s Synth: 350 sec.

46 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 = 0.02 Δ max = 0.05 rock 128×128 δ max = 0.02 Δ max = 0.05 stonewall 200×200 δ max = 0.02 Δ max = 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: sec. Synth: 226 sec. Pre: s Synth: 178 sec. Pre: 6+4 sec. Synth: 427 sec. Pre: sec. Synth: 415 sec. Pre: s Synth: 350 sec.

47 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 = 0.02 Δ max = 0.05 rock 128×128 δ max = 0.02 Δ max = 0.05 stonewall 200×200 δ max = 0.02 Δ max = 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: sec. Synth: 226 sec. Pre: s Synth: 178 sec. Pre: 6+4 sec. Synth: 427 sec. Pre: sec. Synth: 415 sec. Pre: s Synth: 350 sec.

48 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 = 0.02 Δ max = 0.05 rock 128×128 δ max = 0.02 Δ max = 0.05 stonewall 200×200 δ max = 0.02 Δ max = 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: sec. Synth: 226 sec. Pre: s Synth: 178 sec. Pre: 6+4 sec. Synth: 427 sec. Pre: sec. Synth: 415 sec. Pre: s Synth: 350 sec.

49 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 = 0.02 Δ max = 0.05 rock 128×128 δ max = 0.02 Δ max = 0.05 stonewall 200×200 δ max = 0.02 Δ max = 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: sec. Synth: 226 sec. Pre: s Synth: 178 sec. Pre: 6+4 sec. Synth: 427 sec. Pre: sec. Synth: 415 sec. Pre: s Synth: 350 sec.

50 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 = 0.02 Δ max = 0.05 rock 128×128 δ max = 0.02 Δ max = 0.05 stonewall 200×200 δ max = 0.02 Δ max = 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: sec. Synth: 226 sec. Pre: s Synth: 178 sec. Pre: 6+4 sec. Synth: 427 sec. Pre: sec. Synth: 415 sec. Pre: s Synth: 350 sec.

51 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 = 0.02 Δ max = 0.05 rock 128×128 δ max = 0.02 Δ max = 0.05 stonewall 200×200 δ max = 0.02 Δ max = 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: sec. Synth: 226 sec. Pre: s Synth: 178 sec. Pre: 6+4 sec. Synth: 427 sec. Pre: sec. Synth: 415 sec. Pre: s Synth: 350 sec.

52 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

53 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

54 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results Synthesis Comparisons Input Efros/LeungWei/Levoy IQPBSHTS

55 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results Synthesis Comparisons Input Efros/LeungWei/Levoy IQPBSHTS

56 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results Synthesis Comparisons Input Efros/LeungWei/Levoy IQPBSHTS

57 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results Synthesis Comparisons Input Efros/LeungWei/Levoy IQPBSHTS

58 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results Synthesis Comparisons Input Efros/LeungWei/Levoy IQPBSHTS

59 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results Synthesis Comparisons Input Efros/LeungWei/Levoy IQPBSHTS

60 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Results Synthesis Comparisons Input Efros/LeungWei/Levoy IQPBSHTS

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

62 Andrew Nealen and Marc Alexa, Discrete Geometric Modeling Group, TU Darmstadt, 2004 Questions ? Contact Information Andrew Nealen Marc Alexa Matlab code:


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