1. An Algebraic Model for Parameterized Shape Editing Martin Bokeloh, Stanford Univ. Michael Wand, Saarland Univ. & MPI Hans-Peter Seidel, MPI Vladlen Koltun, Stanford University

2. generating variations of individual shape Structure-aware deformation Gal et al 2009. Restricted to deformations with fixed topology Kraevoy et al. 2008

3. generating variations of individual shape Structure-aware deformation Inverse procedural modeling Controllability: finding a production of a shape grammar that fits user constraints remains a difficult problem. Bokeloh et al. 2010Stava et al. 2010

4. generating variations of individual shape Structure-aware deformation Inverse procedural modeling Structure-preserved retargeting Rely on user-provided constraints, and limited to axis- aligned resizing. Lin et al. 2011

5. generating variations of individual shape Structure-aware deformation Inverse procedural modeling Structure-preserved retargeting Pattern-aware shape deformation Bokeloh et al. 2011

6. Pattern-aware Deformation Model Calculus of variations: User constraints Elastic energy Continuous patterns Discrete patterns Does not explicitly model the pattern structure of the object but rather uses elastic deformation to adjust patterns locally.

9. Goal Parameterize an input 3D structure composed of regular patterns so that high-level shape editing that adapts the structure of the shape while maintaining its global characteristics can be supported.

10. Manipulating a single regular pattern A regular pattern P(o, l, t) o - origin of the pattern t - translational symmetry l - number of repetitions o t n=4 Manipulations Change l Change t

11. Parameterizing a structure consists of multiple regular patterns is not easy. (The key: relationships among intersecting patterns)

12. Algebraic Model = Regular patterns + link analysis Decompose the entire input shape into regular patterns

13. Algebraic Model = Regular patterns + link analysis Parameterize each regular pattern

14. Regular Patterns

15. Algebraic Model = Regular patterns + link analysis Detect link relationships among regular patterns

16. Link constraints – pattern constraints (1-1)-interaction, line to line patch: – Collinear: the overlapping interval. – Intersect: the intersection point. (1-2)-interaction, line to area patch: – Coplanar: the overlapping interval. – Intersect: the intersection point. (2-2)-interaction, area to area patch: – Coplanar: the intersection points of the boundaries. – Intersect: (1-1)-interaction. (0-1)- and (0-2)-interactions with rigid patches: – link the origin of the rigid pattern to the intersection line or surface.

17. Algebraic Model = Regular patterns + link analysis The complete shape is represented by a linear system.

18. Algebraic Model = Regular patterns + link analysis The null space of the linear system defines the space of valid variations of the shape.

19. Interactive Constraints: the user selects a pattern element and drags it to a specific target point y. Difference constraints: The user selects two pattern elements, and specifies their difference vector. Regularization constraints: aim to keep the original values of the length variables. Objective function: Shape editing pattern element closest to the selection point Two pattern elements The diff

21. Automated visualization of degrees of freedom for test shapes

29. Limitation restricted to translational regular pattern can only handle rigidly symmetric parts, ruling out organic shapes not consider maintaining irregularity and global symmetries. Can not handle highly detailed geometry with many interleaving patterns