SlideShare a Scribd company logo
Pierre Bénard1,2 Jingwan Lu3 Forrester Cole4
     Adam Finkelstein3    Joëlle Thollot1,2
 1Grenoble   University, LJK   2INRIA   3Princeton   University   4MIT   CSAIL
2
3
• Image space buffers                  • Object space line
      processing                             extraction




Comprehensible rendering of 3-D shapes,   Real-Time Nonphotorealistic Rendering,
  Saito and Takahashi, SIGGRAPH 1990         Markosian et al., SIGGRAPH 1997


4
 Simple and fast
     Natural coherence and LoD
     Restricted stylization effects




                        Implicit Brushes for stylized line-based rendering,
                                                    Vergne et al., CGF 2011
5
 Wide range of styles
     Computationally expensive
     Complex LoD
     No natural coherence



           A Procedural Approach to Style
    for NPR Line Drawing from 3D models,
                    Grabli et al., TOG 2010
6
Line texture


                                    l




    0                  Brush path



7
Fixed Line              View-Dependent Lines




    Creases                      Silhouettes
    Ridges and valleys           Suggestive contours
                                  Apparent ridges
Parameterization = arc-length       Parameterization = ?
                                                           8
• Flatness
         Remain linear in image space
    • Motion coherence
         Evolve according to the motion of the object
    • Temporal continuity
         Adapt to the topological events




9
 Optimization between
                                        2D and 3D
                                       Multiple brush strokes
                                        per line
                                       Dependent on the
                                        input connectivity
     Coherent Stylized Silhouettes,
     Kalnins et al., SIGGRAPH 2003




10
11
Kalnins et al., Coherent Stylized Silhouettes, SIGGRAPH 2003
12
 2D Infinite zoom:
       Self-Similar Line
       Artmap (SLAM)
      Dependent on the
       input connectivity
      One brush stroke
       per line


                     Self-Similar Texture for Coherent Line Stylization,
                                  Bénard et al. NPAR 2010
13
Spatio-Temporal Analysis for
      Ease propagation                 Parameterizing Animated Lines,
       of parameterization                Buchholz et al., NPAR 2011

       with CSS
      Input connectivity




                                       Optimization over the
          Snaxels on a Plane,
                                        entire animation
     Kevin Karsch and John C. Hart,    Offline computation
               NPAR 2011
14
• Image space active contours [Kass et al. 1988]
         Shape
         Topology
         Density

     • Brush paths
         Coherent parameterization
         Shape abstraction

     • Interactive frame rates


15
3D scene                               Feature samples



                                  Image space
                                lines extraction




                                                                  Line drawing
            Snakes
                                     Brush Paths
            Tracking
                                        Geometry
     Advection     Relaxation
                                     Parameterization
          Vectorization
                                        Stylization
     Coverage    Connectivity


16
• Feature samples extracted in image space
        2D position
        Local tangent
        2D velocity




17
3D scene                               Feature samples



                                  Image space
                                lines extraction




                                                                  Line drawing
            Snakes
                                     Brush Paths
            Tracking
                                        Geometry
     Advection     Relaxation
                                     Parameterization
          Vectorization
                                        Stylization
     Coverage    Connectivity


18
Vectorization Tracking


                             Coherence  continuous evolution across frames
                             Accuracy    faithfully representation of shape

                             Coverage    level of detail
                             Simplicity  simple topology
                             Length      stylization freedom




19
• Color regions tracking
       in videos
      Off-line computation
      User corrections

                                 SnakeToonz, Agrawala
                                          NPAR 2002



   Keyframe-Based Tracking for
   Rotoscoping and Animation,
 Agrawala et al. SIGGRAPH 2004
20
• Advection + Relaxation




            Frame f             Frame f+1
21
• Reprojection
      similar to Bousseau et al. 2007 and Lu et al. 2010

     Image f
           f+1




22
• Minimize the energy:



               Internal        External
            – Continuity         Attraction by the
            – Smoothness         features samples

     • Semi-explicit Euler scheme



23
• Grow / shrink
        re-sampling (similar to Delingette et al. 2000)
     • Contour shrinking
        mass-spring forces between the vertices
        almost constant length if no tangential
          external force is applied




24
• Advection + Relaxation




25
• Local vectorization operators




     • Applied sequentially in a greedy fashion
26
27
28
3D scene                               Feature samples



                                  Image space
                                lines extraction




                                                                  Line drawing
            Snakes
                                     Brush Paths
            Tracking
                                        Geometry
     Advection     Relaxation
                                     Parameterization
          Vectorization
                                        Stylization
     Coverage    Connectivity


29
• Linear image space parameterization:

          with   = slope
                 = phase
                 = arc-length
     • Evolve according to the motion and topology
       of the snakes
        parameterization at each vertex


30
• Propagation at each vertex
          Parameterization stored between two frames




31
• Propagation at each vertex
     • Linearization (in the least-square sense)
              parameterization




                                      arc-length


32
• Propagation at each vertex
     • Vectorization events
       Linearization
        Split
        Extend    propagated directly
        Trim
        Merge: mechanism to avoid parameterization
         discontinuities




33
• Only if the slope and phase match
     • Leveling mechanism
                    pushes the 2 parameterizations to their mid-value:

                                                     with
     parameterization




                                                     arc-length

34
35
36
• Segments fitting




37
• Arcs fitting




38
39
40
41
42
43
Input samples                Active strokes




     Robustness toward noise / outliers
      Temporal smoothing
44
• New propagation primitive
          for image space lines
          fully automatic
          running at interactive frame rates
     • Temporally coherent basis for complex effects
           Arc-length variations (texture, offsets, tapering)
           Shape abstraction

45
Thank you for your attention




46

More Related Content

PDF
F045073136
PDF
Learning Moving Cast Shadows for Foreground Detection (VS 2008)
PPSX
Exploring Methods to Improve Edge Detection with Canny Algorithm
PDF
Automated Colorization of Grayscale Images Using Texture Descriptors
PDF
Lm342080283
PDF
Dense Image Matching - Challenges and Potentials (Keynote 3D-ARCH 2015)
PPT
Advanced Lighting Techniques Dan Baker (Meltdown 2005)
PDF
Computationally Efficient NMRF model based Texture Synthesis
F045073136
Learning Moving Cast Shadows for Foreground Detection (VS 2008)
Exploring Methods to Improve Edge Detection with Canny Algorithm
Automated Colorization of Grayscale Images Using Texture Descriptors
Lm342080283
Dense Image Matching - Challenges and Potentials (Keynote 3D-ARCH 2015)
Advanced Lighting Techniques Dan Baker (Meltdown 2005)
Computationally Efficient NMRF model based Texture Synthesis

What's hot (18)

PPTX
Fuzzy Logic Based Edge Detection
PPT
Image segmentation ajal
DOCX
EDGE DETECTION
PPTX
Edge Detection
PDF
Shadow Detection and Removal in Still Images by using Hue Properties of Color...
PDF
Altmann_IGARSS_2011a_talk.pdf
PDF
Study and Comparison of Various Image Edge Detection Techniques
PDF
Ph.D. Thesis Presentation: A Study of Priors and Algorithms for Signal Recove...
PPTX
Edge detection of video using matlab code
PPT
Edges and lines
PDF
Shadow Detection and Removal Techniques A Perspective View
PDF
Edge Detection Using Fuzzy Logic
PPTX
Line detection algorithms
PPTX
Canny edge detection
PDF
PDF
DTAM: Dense Tracking and Mapping in Real-Time, Robot vision Group
DOCX
WBOIT Final Version
PDF
Fingerprint _prem
Fuzzy Logic Based Edge Detection
Image segmentation ajal
EDGE DETECTION
Edge Detection
Shadow Detection and Removal in Still Images by using Hue Properties of Color...
Altmann_IGARSS_2011a_talk.pdf
Study and Comparison of Various Image Edge Detection Techniques
Ph.D. Thesis Presentation: A Study of Priors and Algorithms for Signal Recove...
Edge detection of video using matlab code
Edges and lines
Shadow Detection and Removal Techniques A Perspective View
Edge Detection Using Fuzzy Logic
Line detection algorithms
Canny edge detection
DTAM: Dense Tracking and Mapping in Real-Time, Robot vision Group
WBOIT Final Version
Fingerprint _prem
Ad

Viewers also liked (20)

PPTX
Self-Similar Texture for Coherent Line Stylization, NPAR2010
PDF
Quality Assessment of Fractalized NPR Textures, APGV09
PPTX
Dynamic Solid Textures for Real-Time Coherent Stylization, I3D09
PPSX
Vcdd490 D Mc Gill U5 Breeze5
PDF
Packaging for the future
PPTX
Sustainable agriculture under climate change in the Aral Sea Basin. Maryse Bo...
PDF
Millets And Climate Change, Mar 24, 2010
PPTX
Extension strategies for popularizing millet
PDF
U.S. Organic Millet Market. Analysis and Forecast To 2025
PDF
Millet value chain
PDF
Stored Grain Pest Management
PPTX
Development of composite idly powder using indegenous millets
PDF
Millets, An Old Concept To Adapt To New Change
PDF
Millets For Food And Nutritional Security
PDF
Storage grain insect pests
PPTX
PPTX
Store grain pests A Lecture By Mr Allah Dad Khan
PDF
Ht issue 14 201106
PDF
Wonder World Of Millets
Self-Similar Texture for Coherent Line Stylization, NPAR2010
Quality Assessment of Fractalized NPR Textures, APGV09
Dynamic Solid Textures for Real-Time Coherent Stylization, I3D09
Vcdd490 D Mc Gill U5 Breeze5
Packaging for the future
Sustainable agriculture under climate change in the Aral Sea Basin. Maryse Bo...
Millets And Climate Change, Mar 24, 2010
Extension strategies for popularizing millet
U.S. Organic Millet Market. Analysis and Forecast To 2025
Millet value chain
Stored Grain Pest Management
Development of composite idly powder using indegenous millets
Millets, An Old Concept To Adapt To New Change
Millets For Food And Nutritional Security
Storage grain insect pests
Store grain pests A Lecture By Mr Allah Dad Khan
Ht issue 14 201106
Wonder World Of Millets
Ad

Similar to Active Strokes: Coherent Line Stylization for Animated 3D Models (20)

PDF
Geometry Processingで学ぶSparse Matrix
PDF
Pierre Bénard Ph.D. defense, 2011/07/07
PPTX
SIGGRAPH ASIA 2012 Stereoscopic Cloning Presentation Slide
PDF
CVPR 2012 Review Seminar - Multi-View Hair Capture using Orientation Fields
PPTX
Digital Image Processing Fundamental
PDF
SAL3D presentation - AQSENSE's 3D machine vision library
PPTX
Kintinuous review
PDF
2008 brokerage 03 scalable 3 d models [compatibility mode]
PPTX
Line Detection using Hough transform .pptx
PPTX
Montage4D: Interactive Seamless Fusion of Multiview Video Textures
PPTX
Fcv rep learned-miller
PPTX
Elettronica: Multimedia Information Processing in Smart Environments by Aless...
PDF
Passive stereo vision with deep learning
PPT
Normalized averaging using adaptive applicability functions with applications...
PDF
Four Side Distance: A New Fourier Shape Signature
PDF
lecture_16_jiajun.pdf
PDF
The International Journal of Engineering and Science (The IJES)
PDF
Digital image classification
PPT
Texture Snakes
PDF
Fcv learn sudderth
Geometry Processingで学ぶSparse Matrix
Pierre Bénard Ph.D. defense, 2011/07/07
SIGGRAPH ASIA 2012 Stereoscopic Cloning Presentation Slide
CVPR 2012 Review Seminar - Multi-View Hair Capture using Orientation Fields
Digital Image Processing Fundamental
SAL3D presentation - AQSENSE's 3D machine vision library
Kintinuous review
2008 brokerage 03 scalable 3 d models [compatibility mode]
Line Detection using Hough transform .pptx
Montage4D: Interactive Seamless Fusion of Multiview Video Textures
Fcv rep learned-miller
Elettronica: Multimedia Information Processing in Smart Environments by Aless...
Passive stereo vision with deep learning
Normalized averaging using adaptive applicability functions with applications...
Four Side Distance: A New Fourier Shape Signature
lecture_16_jiajun.pdf
The International Journal of Engineering and Science (The IJES)
Digital image classification
Texture Snakes
Fcv learn sudderth

Recently uploaded (20)

PDF
ENT215_Completing-a-large-scale-migration-and-modernization-with-AWS.pdf
PPTX
observCloud-Native Containerability and monitoring.pptx
PDF
Univ-Connecticut-ChatGPT-Presentaion.pdf
PPTX
Chapter 5: Probability Theory and Statistics
PDF
DASA ADMISSION 2024_FirstRound_FirstRank_LastRank.pdf
PDF
TrustArc Webinar - Click, Consent, Trust: Winning the Privacy Game
PDF
STKI Israel Market Study 2025 version august
PDF
Developing a website for English-speaking practice to English as a foreign la...
PPTX
O2C Customer Invoices to Receipt V15A.pptx
PDF
August Patch Tuesday
PPT
Module 1.ppt Iot fundamentals and Architecture
PPTX
The various Industrial Revolutions .pptx
PPTX
Group 1 Presentation -Planning and Decision Making .pptx
PDF
Assigned Numbers - 2025 - Bluetooth® Document
PDF
Five Habits of High-Impact Board Members
PDF
Unlock new opportunities with location data.pdf
PDF
DP Operators-handbook-extract for the Mautical Institute
PDF
sustainability-14-14877-v2.pddhzftheheeeee
PDF
Getting Started with Data Integration: FME Form 101
PDF
Zenith AI: Advanced Artificial Intelligence
ENT215_Completing-a-large-scale-migration-and-modernization-with-AWS.pdf
observCloud-Native Containerability and monitoring.pptx
Univ-Connecticut-ChatGPT-Presentaion.pdf
Chapter 5: Probability Theory and Statistics
DASA ADMISSION 2024_FirstRound_FirstRank_LastRank.pdf
TrustArc Webinar - Click, Consent, Trust: Winning the Privacy Game
STKI Israel Market Study 2025 version august
Developing a website for English-speaking practice to English as a foreign la...
O2C Customer Invoices to Receipt V15A.pptx
August Patch Tuesday
Module 1.ppt Iot fundamentals and Architecture
The various Industrial Revolutions .pptx
Group 1 Presentation -Planning and Decision Making .pptx
Assigned Numbers - 2025 - Bluetooth® Document
Five Habits of High-Impact Board Members
Unlock new opportunities with location data.pdf
DP Operators-handbook-extract for the Mautical Institute
sustainability-14-14877-v2.pddhzftheheeeee
Getting Started with Data Integration: FME Form 101
Zenith AI: Advanced Artificial Intelligence

Active Strokes: Coherent Line Stylization for Animated 3D Models

  • 1. Pierre Bénard1,2 Jingwan Lu3 Forrester Cole4 Adam Finkelstein3 Joëlle Thollot1,2 1Grenoble University, LJK 2INRIA 3Princeton University 4MIT CSAIL
  • 2. 2
  • 3. 3
  • 4. • Image space buffers • Object space line processing extraction Comprehensible rendering of 3-D shapes, Real-Time Nonphotorealistic Rendering, Saito and Takahashi, SIGGRAPH 1990 Markosian et al., SIGGRAPH 1997 4
  • 5.  Simple and fast  Natural coherence and LoD  Restricted stylization effects Implicit Brushes for stylized line-based rendering, Vergne et al., CGF 2011 5
  • 6.  Wide range of styles  Computationally expensive  Complex LoD  No natural coherence A Procedural Approach to Style for NPR Line Drawing from 3D models, Grabli et al., TOG 2010 6
  • 7. Line texture l 0 Brush path 7
  • 8. Fixed Line View-Dependent Lines  Creases  Silhouettes  Ridges and valleys  Suggestive contours  Apparent ridges Parameterization = arc-length Parameterization = ? 8
  • 9. • Flatness  Remain linear in image space • Motion coherence  Evolve according to the motion of the object • Temporal continuity  Adapt to the topological events 9
  • 10.  Optimization between 2D and 3D  Multiple brush strokes per line  Dependent on the input connectivity Coherent Stylized Silhouettes, Kalnins et al., SIGGRAPH 2003 10
  • 11. 11
  • 12. Kalnins et al., Coherent Stylized Silhouettes, SIGGRAPH 2003 12
  • 13.  2D Infinite zoom: Self-Similar Line Artmap (SLAM)  Dependent on the input connectivity  One brush stroke per line Self-Similar Texture for Coherent Line Stylization, Bénard et al. NPAR 2010 13
  • 14. Spatio-Temporal Analysis for  Ease propagation Parameterizing Animated Lines, of parameterization Buchholz et al., NPAR 2011 with CSS  Input connectivity  Optimization over the Snaxels on a Plane, entire animation Kevin Karsch and John C. Hart,  Offline computation NPAR 2011 14
  • 15. • Image space active contours [Kass et al. 1988]  Shape  Topology  Density • Brush paths  Coherent parameterization  Shape abstraction • Interactive frame rates 15
  • 16. 3D scene Feature samples Image space lines extraction Line drawing Snakes Brush Paths Tracking Geometry Advection Relaxation Parameterization Vectorization Stylization Coverage Connectivity 16
  • 17. • Feature samples extracted in image space  2D position  Local tangent  2D velocity 17
  • 18. 3D scene Feature samples Image space lines extraction Line drawing Snakes Brush Paths Tracking Geometry Advection Relaxation Parameterization Vectorization Stylization Coverage Connectivity 18
  • 19. Vectorization Tracking  Coherence  continuous evolution across frames  Accuracy  faithfully representation of shape  Coverage  level of detail  Simplicity  simple topology  Length  stylization freedom 19
  • 20. • Color regions tracking in videos  Off-line computation  User corrections SnakeToonz, Agrawala NPAR 2002 Keyframe-Based Tracking for Rotoscoping and Animation, Agrawala et al. SIGGRAPH 2004 20
  • 21. • Advection + Relaxation Frame f Frame f+1 21
  • 22. • Reprojection similar to Bousseau et al. 2007 and Lu et al. 2010 Image f f+1 22
  • 23. • Minimize the energy: Internal External – Continuity Attraction by the – Smoothness features samples • Semi-explicit Euler scheme 23
  • 24. • Grow / shrink  re-sampling (similar to Delingette et al. 2000) • Contour shrinking  mass-spring forces between the vertices  almost constant length if no tangential external force is applied 24
  • 25. • Advection + Relaxation 25
  • 26. • Local vectorization operators • Applied sequentially in a greedy fashion 26
  • 27. 27
  • 28. 28
  • 29. 3D scene Feature samples Image space lines extraction Line drawing Snakes Brush Paths Tracking Geometry Advection Relaxation Parameterization Vectorization Stylization Coverage Connectivity 29
  • 30. • Linear image space parameterization: with = slope = phase = arc-length • Evolve according to the motion and topology of the snakes  parameterization at each vertex 30
  • 31. • Propagation at each vertex  Parameterization stored between two frames 31
  • 32. • Propagation at each vertex • Linearization (in the least-square sense) parameterization arc-length 32
  • 33. • Propagation at each vertex • Vectorization events Linearization  Split  Extend propagated directly  Trim  Merge: mechanism to avoid parameterization discontinuities 33
  • 34. • Only if the slope and phase match • Leveling mechanism pushes the 2 parameterizations to their mid-value: with parameterization arc-length 34
  • 35. 35
  • 36. 36
  • 39. 39
  • 40. 40
  • 41. 41
  • 42. 42
  • 43. 43
  • 44. Input samples Active strokes Robustness toward noise / outliers  Temporal smoothing 44
  • 45. • New propagation primitive  for image space lines  fully automatic  running at interactive frame rates • Temporally coherent basis for complex effects  Arc-length variations (texture, offsets, tapering)  Shape abstraction 45
  • 46. Thank you for your attention 46