Pierre BénardJoëlle ThollotGrenoble Universities / INRIA Rhône-AlpesAres Lagae<br />KatholiekeUniversiteit LeuvenREVES - I...
Stylization of 3D Animations<br />3D scene  2D appearance<br />2<br />
Stylization of 3D Animations<br />3D scene  2D appearance<br />Stylized color regions<br />2D medium: a pattern<br />Temp...
Hand–made animation<br />« Il pleut bergère », Jérémy Depuydt (2005)<br />4<br />PoppingTemporal continuity<br />
Naïve CG solutions<br />5<br />Shower-door effect<br /> Coherent Motion<br />Traditional mapping<br /> Flatness<br />
Temporal Coherence Problem<br />Extreme cases  Requirements<br />6<br />Flatness<br />Shower-door<br />Popping<br />Coher...
3 goals to ensure at best<br />Additional challenges<br />Flexibility 		 	variety of styles<br />Interactivity 	 	artist...
Previous Work<br />
Texture-Based methods<br />Object-space<br /><ul><li>Blending artifacts
Perspective distortion</li></ul>Flatness<br />[BBT09]<br />Popping<br />Shower-door<br />Coherent motion<br />Temporal con...
Texture-Based methods<br />Object-space<br />Screen-space<br /><ul><li>Sliding</li></ul>Flatness<br />Screen-space texture...
Few-Primitive methods<br /><ul><li>Clutter / holes
Popping</li></ul>11<br />or<br />Flatness<br />[Mei96]<br />Few-primitive methods [Mei96,Dan99,HE04,VBTS07]<br />Screen-sp...
Few-Primitive methods<br />12<br />Vanderhaeghe et al. EGSR 2007<br />
Key Insight<br />Blending a large number of primitives<br />Reduce popping artifacts<br />Individual primitives merge  te...
Many-Primitive methods<br />[KC05]<br />Flatness<br />Few-primitive methods [Mei96,Dan99,HE04,VBTS07]<br />Screen-space te...
NPR Gabor Noise<br />
Procedural noises<br />Sparse convolution [Lewis 84,89]<br />Spot Noise [van Wijk 91]<br />Gabor Noise [LLDD09]<br /> Our...
Gabor Noise [LLDD09]<br />Offers significant spectral control<br />Support anisotropy<br />Is fast to evaluate<br />17<br ...
Gabor Noise [LLDD09]<br />Definition<br />Sum of randomly positioned and weighted kernels<br />18<br />Gabor kernel<br />n...
NPR Gabor Noise<br />Basic principles follow from the goals<br />Flatness<br /><ul><li> Noise parameters in 2D screen space
 Evaluation in 2D screen space</li></ul>19<br />2D Gabor noise [LLDD09]<br />
NPR Gabor Noise<br />Basic principles follow from the goals<br />Flatness<br />Coherent motion<br /><ul><li>Point distribu...
NPR Gabor Noise<br />Basic principles follow from the goals<br />Flatness<br />Coherent motion<br />21<br />Surface Gabor ...
NPR Gabor Noise<br />Basic principles follow from the goals<br />Flatness<br />Coherent motion<br />Continuity<br /><ul><l...
GPU Splatting Algorithm<br />Sample 3D triangles<br />2D Poisson distribution with constant screen space density<br />PRNG...
less points</li></ul>Close<br /><ul><li>large screen area
more points</li></li></ul><li>GPU Splatting Algorithm<br />Generate 2D point sprites<br />24<br />Point distribution<br />...
LOD Mechanism<br />Blending scheme using statistical properties<br />Reduce popping<br />Preserve noise appearance<br />25...
Styles<br />
Style Design<br />Standard techniques from procedural texturing and modeling [EMPPW02]<br />Threshold <br />Smooth step fu...
Style Design<br />28<br />
Results:<br />29<br />isotropic as well asanisotropic patterns<br />
30<br />local variation	according to shading<br />Results:<br />
31<br />local orientation guided 	  by surface curvature<br />Results:<br />
User Study<br />
User Study: Motivation<br />Evaluate success of various solutions according to<br />Relative importance of these criteria<...
User Study: Setup<br />Methodology<br />15 naïve subjects, ~ 20-30 minutes<br />Ranking tasks<br />“Rank the images/videos...
User Study: Compared methods<br />35<br />Local screen-space<br />Global screen-space<br />Object-space<br />Adv<br />D2D<...
User Study: Flatness<br />Adv<br />D2D<br />DST<br />ours<br />SD<br />TM<br />Simple stimuli<br />36<br />Object-space<br />
User Study: Flatness<br />Complex stimuli<br />Adv<br />D2D<br />DST<br />ours<br />SD<br />TM<br />37<br />
User Study: Flatness<br />“Rank the images according to how flat they appear.”<br />Simple stimuli<br /><ul><li>Image-spac...
Object-space methods less flat</li></ul>Complex stimuli<br /><ul><li> High variance  confusing question
 Many 3D cues  flatness not perceived</li></ul>38<br />
Simple stimuli<br />User Study: Dynamic stimuli<br />39<br />
Complex stimuli<br />User Study: Dynamic stimuli<br />40<br />
User Study: Coherent motion<br />“Rank the videos according to how coherently the pattern moves with the object.”<br />Sim...
Shower-door least coherent
Image-space methods provide a tradeoff</li></ul>Complex stimuli<br /><ul><li>Same conclusions
Our approach slightly betterthan other image-space methods</li></ul>41<br />
“Rank the videos according to how much the pattern changes over time.”<br />Simple stimuli<br /><ul><li>High variance
Advection and ours produce more changes
 “swimming” artifacts</li></ul>Complex stimuli<br /><ul><li>Shower door and D2D least changes
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A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

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Presentation of our paper called "A Dynamic Noise Primitive for Coherent Stylization" published at EGSR 2010

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  • In complement to our analysis of previous work on the triangle of requirements, we would like to evaluate how final viewers actually perceive these tradeoffs. We believe that such study can provide significant insight into how well previous solutions, including ours, perform for each goal: flatness: how much is the pattern perceived as produced in 2D coherent motion: how closely is the pattern following the 3D motion of the scene and temporal continuity: how much does the pattern change over timeBesides, this study may give an indication of the relative importance of these criteria. That is if the choice of an equilateral triangle is meaningful.
  • The results for motion coherence and pleasantness exhibits least variance and are strongly correlated.This indicates that motion coherence is probably the most important quality to preserve in the overall temporal coherence compromise.Both Dynamic Solid Textures and our method perform well on the motion coherence scale: the first one trades off better temporal continuity, whereas ours trades off better flatness.
  • A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

    1. 1. Pierre BénardJoëlle ThollotGrenoble Universities / INRIA Rhône-AlpesAres Lagae<br />KatholiekeUniversiteit LeuvenREVES - INRIA Sophia-Antipolis<br />Peter VangorpGeorge DrettakisREVES - INRIA Sophia-AntipolisSylvain LefebvreALICE - INRIA Nancy / Loria<br />A Dynamic Noise Primitive for Coherent Stylization<br />
    2. 2. Stylization of 3D Animations<br />3D scene  2D appearance<br />2<br />
    3. 3. Stylization of 3D Animations<br />3D scene  2D appearance<br />Stylized color regions<br />2D medium: a pattern<br />Temporal coherence<br />3<br />Paint strokes<br />Pencil strokes<br />Paper<br />Watercolor pigments<br />
    4. 4. Hand–made animation<br />« Il pleut bergère », Jérémy Depuydt (2005)<br />4<br />PoppingTemporal continuity<br />
    5. 5. Naïve CG solutions<br />5<br />Shower-door effect<br /> Coherent Motion<br />Traditional mapping<br /> Flatness<br />
    6. 6. Temporal Coherence Problem<br />Extreme cases  Requirements<br />6<br />Flatness<br />Shower-door<br />Popping<br />Coherent motion<br />Temporal continuity<br />Traditional mapping<br />Contradictory requirements:<br />solution  find a compromise<br />
    7. 7. 3 goals to ensure at best<br />Additional challenges<br />Flexibility  variety of styles<br />Interactivity  artistic control<br />Evaluation  quality of the trade-off<br />Flatness<br />Coherent motion<br />Temporal continuity<br />7<br />
    8. 8. Previous Work<br />
    9. 9. Texture-Based methods<br />Object-space<br /><ul><li>Blending artifacts
    10. 10. Perspective distortion</li></ul>Flatness<br />[BBT09]<br />Popping<br />Shower-door<br />Coherent motion<br />Temporal continuity<br />Object-space texture mapping[KLK*00,PHWF01,FMS01,BBT09]<br />Traditional mapping<br />9<br />
    11. 11. Texture-Based methods<br />Object-space<br />Screen-space<br /><ul><li>Sliding</li></ul>Flatness<br />Screen-space texture mapping[CTP*03,CDH06,BSM*07,BNTS07]<br />Popping<br />[CTP*03]<br />Coherent motion<br />Temporal continuity<br />Object-space texture mapping[KLK*00,PHWF01,FMS01,BBT09]<br />10<br />Shower-door<br />
    12. 12. Few-Primitive methods<br /><ul><li>Clutter / holes
    13. 13. Popping</li></ul>11<br />or<br />Flatness<br />[Mei96]<br />Few-primitive methods [Mei96,Dan99,HE04,VBTS07]<br />Screen-space texture mapping[CTP*03,CDH06,BSM*07,BNTS07]<br />Popping<br />Coherent motion<br />Temporal continuity<br />Object-space texture mapping[KLK*00,PHWF01,FMS01,BBT09]<br />
    14. 14. Few-Primitive methods<br />12<br />Vanderhaeghe et al. EGSR 2007<br />
    15. 15. Key Insight<br />Blending a large number of primitives<br />Reduce popping artifacts<br />Individual primitives merge  texture<br />13<br />
    16. 16. Many-Primitive methods<br />[KC05]<br />Flatness<br />Few-primitive methods [Mei96,Dan99,HE04,VBTS07]<br />Screen-space texture mapping[CTP*03,CDH06,BSM*07,BNTS07]<br />Many-primitive methods[KC05,BKTS06]<br />Coherent motion<br />Temporal continuity<br />14<br />Object-space texture mapping[KLK*00,PHWF01,FMS01,BBT09]<br />
    17. 17. NPR Gabor Noise<br />
    18. 18. Procedural noises<br />Sparse convolution [Lewis 84,89]<br />Spot Noise [van Wijk 91]<br />Gabor Noise [LLDD09]<br /> Our trade-off: NPR Gabor Noise<br />16<br />
    19. 19. Gabor Noise [LLDD09]<br />Offers significant spectral control<br />Support anisotropy<br />Is fast to evaluate<br />17<br />See “State of the Art in Procedural Noise Functions”, EG 2010 for comparisons with previous work<br />
    20. 20. Gabor Noise [LLDD09]<br />Definition<br />Sum of randomly positioned and weighted kernels<br />18<br />Gabor kernel<br />noise<br />random positionsand weights<br />
    21. 21. NPR Gabor Noise<br />Basic principles follow from the goals<br />Flatness<br /><ul><li> Noise parameters in 2D screen space
    22. 22. Evaluation in 2D screen space</li></ul>19<br />2D Gabor noise [LLDD09]<br />
    23. 23. NPR Gabor Noise<br />Basic principles follow from the goals<br />Flatness<br />Coherent motion<br /><ul><li>Point distribution on the surface of the 3D model</li></ul>20<br />Surface Gabor noise [LLDD09]<br />2D Gabor noise [LLDD09]<br />
    24. 24. NPR Gabor Noise<br />Basic principles follow from the goals<br />Flatness<br />Coherent motion<br />21<br />Surface Gabor noise [LLDD09]<br />NPR Gabor noise<br />2D Gabor noise [LLDD09]<br />
    25. 25. NPR Gabor Noise<br />Basic principles follow from the goals<br />Flatness<br />Coherent motion<br />Continuity<br /><ul><li> Smooth LOD mechanism</li></ul>22<br />Surface Gabor noise [LLDD09]<br />NPR Gabor noise<br />2D Gabor noise [LLDD09]<br />
    26. 26. GPU Splatting Algorithm<br />Sample 3D triangles<br />2D Poisson distribution with constant screen space density<br />PRNG: seed = triangle ID<br />23<br />Far<br /><ul><li>small screen area
    27. 27. less points</li></ul>Close<br /><ul><li>large screen area
    28. 28. more points</li></li></ul><li>GPU Splatting Algorithm<br />Generate 2D point sprites<br />24<br />Point distribution<br />Texture sprites<br />
    29. 29. LOD Mechanism<br />Blending scheme using statistical properties<br />Reduce popping<br />Preserve noise appearance<br />25<br />
    30. 30. Styles<br />
    31. 31. Style Design<br />Standard techniques from procedural texturing and modeling [EMPPW02]<br />Threshold <br />Smooth step function <br />X-toon textures [BTM06]<br />Compositing (alpha-blending, overlay)<br />Local control<br />Curvature  noise orientation<br />Shading  noise frequency<br />Interactivefeedback<br />Threshold texture<br />27<br />
    32. 32. Style Design<br />28<br />
    33. 33. Results:<br />29<br />isotropic as well asanisotropic patterns<br />
    34. 34. 30<br />local variation according to shading<br />Results:<br />
    35. 35. 31<br />local orientation guided by surface curvature<br />Results:<br />
    36. 36. User Study<br />
    37. 37. User Study: Motivation<br />Evaluate success of various solutions according to<br />Relative importance of these criteria<br />33<br />Flatness<br />Coherent motion<br />Temporal continuity<br />
    38. 38. User Study: Setup<br />Methodology<br />15 naïve subjects, ~ 20-30 minutes<br />Ranking tasks<br />“Rank the images/videos according to … ”<br />34<br />
    39. 39. User Study: Compared methods<br />35<br />Local screen-space<br />Global screen-space<br />Object-space<br />Adv<br />D2D<br />DST<br />ours<br />SD<br />TM<br />Extreme cases<br />
    40. 40. User Study: Flatness<br />Adv<br />D2D<br />DST<br />ours<br />SD<br />TM<br />Simple stimuli<br />36<br />Object-space<br />
    41. 41. User Study: Flatness<br />Complex stimuli<br />Adv<br />D2D<br />DST<br />ours<br />SD<br />TM<br />37<br />
    42. 42. User Study: Flatness<br />“Rank the images according to how flat they appear.”<br />Simple stimuli<br /><ul><li>Image-space methods more flat
    43. 43. Object-space methods less flat</li></ul>Complex stimuli<br /><ul><li> High variance  confusing question
    44. 44. Many 3D cues  flatness not perceived</li></ul>38<br />
    45. 45. Simple stimuli<br />User Study: Dynamic stimuli<br />39<br />
    46. 46. Complex stimuli<br />User Study: Dynamic stimuli<br />40<br />
    47. 47. User Study: Coherent motion<br />“Rank the videos according to how coherently the pattern moves with the object.”<br />Simple stimuli<br /><ul><li>Object-space methods more coherent
    48. 48. Shower-door least coherent
    49. 49. Image-space methods provide a tradeoff</li></ul>Complex stimuli<br /><ul><li>Same conclusions
    50. 50. Our approach slightly betterthan other image-space methods</li></ul>41<br />
    51. 51. “Rank the videos according to how much the pattern changes over time.”<br />Simple stimuli<br /><ul><li>High variance
    52. 52. Advection and ours produce more changes
    53. 53. “swimming” artifacts</li></ul>Complex stimuli<br /><ul><li>Shower door and D2D least changes
    54. 54. Others perceived equally</li></ul>User Study: Temporal continuity<br />42<br />
    55. 55. User Study: Pleasantness<br />“Rank the videos according to how pleasant you find them in the context of cartoon animation.”<br />Complex stimuli<br /><ul><li>Object-space approaches more pleasant
    56. 56. Our methods firstimage-space approaches</li></ul>43<br />
    57. 57. User Study: Pleasantness<br />Strong correlation with “motion coherence”<br /><ul><li>most important criteria to preserve</li></ul>NPR Gabor noise performs well<br />44<br />
    58. 58. Conclusions and Future Work<br />45<br />
    59. 59. User Study<br /><ul><li>First step toward formal evaluation
    60. 60. Flatness hard to see in complex scenes
    61. 61. Motion coherence predominant criteria</li></ul>Intrinsic limitations<br />Hatching  other styles<br />Naïve users  professional artists<br />Objective metric<br />Statistical texture measures [BTS09]<br />Optical flow analysis<br />46<br />
    62. 62. NPR Gabor Noise<br />New primitive for coherent stylization<br />Interactive scheme:remaining popping<br /><ul><li>“Procedural” evaluation [LLDD09]</li></ul>Slower, but should avoid popping<br />Useful for high quality offline rendering<br />Temporally coherent spot noise<br /><ul><li>Additional patterns</li></ul>47<br />
    63. 63. Thanks!<br />Styles cookbook and experiment stimuli:<br />http://artis.inrialpes.fr/Publications/2010/BLVLDT10<br />Acknowledgments<br /><ul><li>Laurence Boissieux, Kartic Subr, Adrien Bousseau and Marcio Cabral
    64. 64. The participants of the study
    65. 65. Research Foundation-Flanders (FWO), CREA (K.U.Leuven)</li></li></ul><li>
    66. 66. User Study: Flatness<br />“Rank the images according to how flat they appear.”<br />Simple stimuli<br />Complex stimuli<br />less flat<br />more flat<br />less flat<br />more flat<br />50<br />50<br />
    67. 67. User Study: Coherent motion<br />“Rank the videos according to how coherently the pattern moves with the object.”<br />Simple stimuli<br />Complex stimuli<br />Object-space<br />translate:<br />rotate:<br />zoom:<br />more coherent<br />less coherent<br />less coherent<br />more coherent<br />51<br />
    68. 68. “Rank the videos according to how much the pattern changes over time.”<br />Simple stimuli<br />Complex stimuli<br />User Study: Temporal continuity<br />translate:<br />rotate:<br />zoom:<br />more change<br />less change<br />more change<br />less change<br />52<br />52<br />
    69. 69. User Study: Pleasantness<br />“Rank the videos according to how pleasant you find them in the context of cartoon animation.”<br />Complex stimuli<br />Object-space<br />less pleasant<br />more pleasant<br />80<br />53<br />

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