a dynamic noise primitive for coherent stylization, egsr 2010

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A DYNAMIC NOISE PRIMITIVE FOR COHERENT STYLIZATION Pierre Bénard Joëlle Thollot Grenoble Universities / INRIA Rhône-Alpes Ares Lagae Katholieke Universiteit Leuven REVES - INRIA Sophia-Antipolis Peter Vangorp George Drettakis REVES - INRIA Sophia-Antipolis Sylvain Lefebvre ALICE - INRIA Nancy / Loria

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

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Page 1: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

A DYNAMIC NOISE PRIMITIVE

FOR COHERENT STYLIZATION

Pierre BénardJoëlle ThollotGrenoble Universities / INRIA Rhône-Alpes

Ares LagaeKatholieke Universiteit LeuvenREVES - INRIA Sophia-Antipolis

Peter VangorpGeorge DrettakisREVES - INRIA Sophia-Antipolis

Sylvain LefebvreALICE - INRIA Nancy / Loria

Page 2: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Stylization of 3D Animations• 3D scene 2D appearance

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Page 3: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Stylization of 3D Animations• 3D scene 2D appearance

• Stylized color regions– 2D medium: a pattern– Temporal coherence

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Paper

Pencil strokes

Watercolor pigments

Paint strokes

Page 4: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Hand –made animation« Il pleut bergère », Jérém

y Depuydt (2005)

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Popping Temporal continuity

Page 5: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Naïve CG solutions

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Shower-door effect Coherent Motion

Traditional mapping Flatness

Page 6: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Temporal Coherence Problem• Extreme cases Requirements

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Coherent motion Temporal continuity

Flatness

Traditional mapping

Shower-doorPopping

Contradictory requirements:solution find a compromise

Page 7: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

3 goals to ensure at best

• Additional challenges– Flexibility variety of styles– Interactivity artistic control– Evaluation quality of the trade-off

Coherent motion Temporal continuity

Flatness

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Page 8: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

PREVIOUS WORK

Page 9: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Texture -Based methods• Object-space Blending artifacts Perspective distortion

Coherent motion

Temporal continuity

Flatness

Traditional mapping

Shower-doorPopping

Object-space texture mapping[KLK*00,PHWF01,FMS01,BBT09]

[BBT09]

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Page 10: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Texture -Based methods• Object-space• Screen-space Sliding

Coherent motion

Temporal continuity

Flatness

Popping

[CTP*03]

Screen-space texture mapping[CTP*03,CDH06,BSM*07,BNTS07]

Object-space texture mapping[KLK*00,PHWF01,FMS01,BBT09] 10

Shower-door

Page 11: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Few -Primitive methods Clutter / holes Popping

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Coherent motion

Temporal continuity

Flatness

Popping

[Mei96]

Few-primitive methods [Mei96,Dan99,HE04,VBTS07]

Object-space texture mapping[KLK*00,PHWF01,FMS01,BBT09]

Screen-space texture mapping[CTP*03,CDH06,BSM*07,BNTS07]

or

Page 12: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Few -Primitive methods

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Vanderhaeghe et al. EGSR 2007

Page 13: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Key Insight• Blending a large number of primitives

– Reduce popping artifacts– Individual primitives merge texture

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Page 14: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Many-Primitive methods

Coherent motion

Temporal continuity

Flatness

[KC05]

Many-primitive methods[KC05,BKTS06]

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Object-space texture mapping[KLK*00,PHWF01,FMS01,BBT09]

Few-primitive methods [Mei96,Dan99,HE04,VBTS07]

Screen-space texture mapping[CTP*03,CDH06,BSM*07,BNTS07]

Page 15: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

NPR GABOR NOISE

Page 16: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Procedural noises• Sparse convolution [Lewis 84,89]• Spot Noise [van Wijk 91]• Gabor Noise [LLDD09]

Our trade-off: NPR Gabor Noise

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Page 17: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Gabor Noise [LLDD09]• Offers significant spectral control• Support anisotropy• Is fast to evaluate

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See “State of the Art in Procedural Noise Functions”, EG 2010 for comparisons with previous work

Page 18: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Gabor Noise [LLDD09]• Definition

Sum of randomly positioned and weighted kernels

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Gabor kernel noiserandom positionsand weights

Page 19: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

NPR Gabor Noise• Basic principles follow from the goals

– Flatness Noise parameters in 2D screen space Evaluation in 2D screen space

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2D Gabor noise [LLDD09]

Page 20: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

NPR Gabor Noise• Basic principles follow from the goals

– Flatness– Coherent motion

Point distribution on the surface of the 3D model

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Surface Gabor noise [LLDD09]

2D Gabor noise [LLDD09]

Page 21: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

NPR Gabor Noise• Basic principles follow from the goals

– Flatness– Coherent motion

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Surface Gabor noise [LLDD09]

NPR Gabor noise2D Gabor noise [LLDD09]

Page 22: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

NPR Gabor Noise• Basic principles follow from the goals

– Flatness– Coherent motion– Continuity

Smooth LOD mechanism

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Surface Gabor noise [LLDD09]

NPR Gabor noise2D Gabor noise [LLDD09]

Page 23: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

GPU Splatting Algorithm• Sample 3D triangles

– 2D Poisson distribution with constant screen space density

– PRNG: seed = triangle ID

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Farsmall screen

arealess points

Closelarge screen

areamore points

Page 24: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

GPU Splatting Algorithm• Generate 2D point sprites

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Point distribution Texture sprites

Page 25: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

LOD Mechanism• Blending scheme using statistical properties

– Reduce popping– Preserve noise appearance

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Page 26: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

STYLES

Page 27: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Style Design• Standard techniques from procedural texturing

and modeling [EMPPW02]– Threshold

• Smooth step function • X-toon textures [BTM06]

– Compositing (alpha-blending, overlay)– Local control

• Curvature noise orientation• Shading noise frequency

• Interactive feedback

Threshold texture

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Page 28: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Style Design

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Page 29: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Results :

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isotropic as well asanisotropic patterns

Page 30: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

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Results :local variationaccording to shading

Page 31: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Results :

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local orientation guided by surface curvature

Page 32: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

USER STUDY

Page 33: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Motivation• Evaluate success of various solutions

according to

• Relative importance of these criteria

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Coherent motion Temporal continuity

Flatness

Page 34: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Setup• Methodology

– 15 naïve subjects, ~ 20-30 minutes• Ranking tasks

“Rank the images/videos according to … ”

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Page 35: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Compared methods

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Adv D2D DST

ours SD TM

Extreme cases

Local screen-spaceGlobal screen-space Object-space

Page 36: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Flatness• Simple stimuli

Adv D2D DST

ours SD TM

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Object-space

Page 37: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Flatness• Complex stimuli

Adv D2D DST

ours SD TM

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Page 38: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Flatness“Rank the images according to

how flat they appear.”• Simple stimuli

– Image-space methods more flat– Object-space methods less flat

• Complex stimuli– High variance confusing question– Many 3D cues flatness not perceived

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Page 39: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

• Simple stimuli

User Study: Dynamic stimuli

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Page 40: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

• Complex stimuli

User Study: Dynamic stimuli

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Page 41: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Coherent motion“Rank the videos according to how coherently

the pattern moves with the object.”• Simple stimuli

– Object-space methods more coherent– Shower-door least coherent– Image-space methods provide a tradeoff

• Complex stimuli– Same conclusions– Our approach slightly better than other

image-space methods41

Page 42: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

“Rank the videos according to how much the pattern changes over time.”

• Simple stimuli– High variance– Advection and ours produce more changes

“swimming” artifacts

• Complex stimuli– Shower door and D2D least changes– Others perceived equally

User Study: Temporal continuity

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Page 43: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Pleasantness“Rank the videos according to how

pleasant you find them in the context of cartoon animation.”

• Complex stimuli– Object-space approaches more pleasant– Our methods first image-space approaches

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Page 44: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Pleasantness• Strong correlation with “motion coherence”

most important criteria to preserve

• NPR Gabor noise performs well

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Page 45: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

CONCLUSIONSAND FUTURE WORK

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Page 46: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study• First step toward formal evaluation

– Flatness hard to see in complex scenes– Motion coherence predominant criteria

• Intrinsic limitations– Hatching other styles– Naïve users professional artists

• Objective metric– Statistical texture measures [BTS09]– Optical flow analysis

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Page 47: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

NPR Gabor Noise

• New primitive for coherent stylization

• Interactive scheme: remaining popping “Procedural” evaluation [LLDD09]

– Slower, but should avoid popping– Useful for high quality offline rendering

• Temporally coherent spot noise Additional patterns

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Page 48: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

Thanks !

Styles cookbook and experiment stimuli:

http://artis.inrialpes.fr/Publications/2010/BLVLDT10

Acknowledgments• Laurence Boissieux, Kartic Subr, Adrien Bousseau and Marcio Cabral• The participants of the study• Research Foundation-Flanders (FWO), CREA (K.U.Leuven)

Page 49: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010
Page 50: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Flatness• “Rank the images according to how flat

they appear.”– Simple stimuli

– Complex stimuli

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less flat more flat

DST TM Adv ours SD D2D

less flat more flat

TM SD DST ours D2D Adv

50

Page 51: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Coherent motion• “Rank the videos according to how coherently

the pattern moves with the object.”– Simple stimuli

– Complex stimuliless coherent more coherent

SD D2D ours Adv DST TM

SD D2D Adv ours TM DST

SD Adv D2D ours TM DST

SD Adv ours D2D TM DST

translate:

rotate:

zoom:

less coherent more coherent

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Object-space

Page 52: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

• “Rank the videos according to how much the pattern changes over time.”– Simple stimuli

– Complex stimuli

User Study: Temporal continuity

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Adv ours D2D DST TM SD

TM DST ours Adv D2D SD

Adv SD TM DST ours D2D

Adv ours D2D DST SD TM

more change less change

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translate:

rotate:

zoom:

more change less change

Page 53: A Dynamic Noise Primitive for Coherent Stylization, EGSR 2010

User Study: Pleasantness• “Rank the videos according to how

pleasant you find them in the context of cartoon animation.”– Complex stimuli

80

SD D2D Adv ours DST TM

less pleasant more pleasant

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Object-space