HelpingHand : Example-based Stroke Stylization

1. HelpingHand: Example-based Stroke Stylization Presenter: Feilongyan Jingwan Lu Princeton University Fisher Yu Princeton University Adam Finkelstein Princeton University Stephen DiVerdi Adobe Systems Inc.

2. Painting Device A high quality stylus has 6 degrees of freedom (DOFs: 2D position, pressure, 2D tilt, and 1D rotation) (Note , at every point of trajectory)

3. Examples of 6DOF 2D trajectory alone 6DoF A Painting with 6DoF

4. Current Problems • Such devices are difficult for novices to control • The devices with 6DoFs are relatively expensive Is it possible to achieve 6DoFs withlow quality devices and by novices?

5. This Paper • Present a data driven method for synthesizing plausible pose data, optionally for synthesizing the stroke trajectory style.

6. This Paper • Present a data driven method for synthesizing plausible pose data, optionally for synthesizing the stroke trajectory style. • Two underpinning assumptions observed:

7. This Paper • Present a data driven method for synthesizing plausible pose data, optionally for synthesizing the stroke trajectory style. • Two underpinning assumptions observed: • Strokes of the same artist with similar trajectory are drawn with similar hand pose (for Pose Synthesis)

8. This Paper • Present a data driven method for synthesizing plausible pose data, optionally for synthesizing the stroke trajectory style. • Two underpinning assumptions observed: • Strokes of the same artist with similar trajectory are drawn with similar hand pose (for Pose Synthesis) • Shapes of strokes are part of the “style” of a given artist (for Trajectory synthesis)

9. Connection • With these two assumptions , we can use trajectory of stroke to query the library, whether pose or trajectory synthesis, the trajectory may be used to query

10. Data Driven Approach Pose Synthesis Pose and Trajectory Synthesis Query (2DoFs) Pose & Trajectory Synthesis Output Online Library of 6DoFs Strokes (By Artists) Offline

11. Offline • Collect a library of strokes with 6D data by trained artists • Compute the shape Feature Vectors (such as shape context) for every sample of the strokes, as the descriptor for comparison

12. Online • Stroke by stroke • Compute the feature vectors for samples of the current query stroke • With feature vector, search for the K-NN for every sample. • For the current stroke, get the optimal sample sequencefrom library using Dynamic programming • Pose synthesis or trajectory synthesis

13. Result

14. Paper Stylization Query (poor exposition) Sentence Synthesis Desired Paper Online Library of Beautiful Sentences Offline

15. Thank You