Programmable Animation Texturing using Motion Stamps

Our work on programmable animation texturing enhances the concept of texture mapping by letting artists stylize arbitrary animations using elementary animations, instantiated at the scale of their choice. The core of our workflow resides in two components: we first impose structure and temporal coherence over the animation data using a novel radius‐based animation‐aware clustering. The computed clusters conform to the user‐specified scale, and follow the underlying animation regardless of its topology. Extreme mesh deformations, complex particle simulations, or simulated mesh animations with ever‐changing topology can therefore be handled in a temporally coherent way. Then, in analogy to fragment shaders that specify an output color based on a texture and a collection of properties defined per vertex (position, texture coordinate, etc.), we provide a programmable interface to the user, letting him or her specify an output animation based on the collection of properties we extract per cluster (position, velocity, etc.). We equip elementary animations with a collection of parameters that are exposed in our programmable system and enables users to script the animated textures depending on properties of the input cluster. We demonstrate the power of our system with complex animated textures created with minimal user input.

[1]  Christian S. Jensen,et al.  Discovery of convoys in trajectory databases , 2008, Proc. VLDB Endow..

[2]  Beng Chin Ooi,et al.  Continuous Clustering of Moving Objects , 2007, IEEE Transactions on Knowledge and Data Engineering.

[3]  Stephen Chenney,et al.  Cartoon rendering of smoke animations , 2004, NPAR '04.

[4]  James F. O'Brien,et al.  Example-based wrinkle synthesis for clothing animation , 2010, ACM Trans. Graph..

[5]  Ming C. Lin,et al.  Fast animation of turbulence using energy transport and procedural synthesis , 2008, SIGGRAPH Asia '08.

[6]  Edilson de Aguiar,et al.  Stable spaces for real-time clothing , 2010, ACM Trans. Graph..

[7]  Markus H. Gross,et al.  Hierarchical motion brushes for animation instancing , 2014, NPAR '14.

[8]  Greg Turk,et al.  Controlling liquids using meshes , 2012, SCA '12.

[9]  Peter-Pike J. Sloan,et al.  Physics-inspired upsampling for cloth simulation in games , 2011, ACM Trans. Graph..

[10]  Eitan Grinspun,et al.  Example-based elastic materials , 2011, ACM Trans. Graph..

[11]  Lin Shi,et al.  Controllable smoke animation with guiding objects , 2005, TOGS.

[12]  Yoshinori Dobashi,et al.  Feedback control of cumuliform cloud formation based on computational fluid dynamics , 2008, ACM Trans. Graph..

[13]  Nadia Magnenat-Thalmann,et al.  Animating wrinkles on clothes , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).

[14]  Li-yi Wei,et al.  Discrete element textures , 2011, SIGGRAPH 2011.

[15]  Adrien Treuille,et al.  Keyframe control of smoke simulations , 2003, ACM Trans. Graph..

[16]  Doug L. James,et al.  Wavelet turbulence for fluid simulation , 2008, SIGGRAPH 2008.

[17]  Yee-Hong Yang,et al.  Modeling water for computer graphics , 1997, Comput. Graph..

[18]  Sariel Har-Peled Clustering Motion , 2004, Discret. Comput. Geom..

[19]  Yifan Li,et al.  Clustering moving objects , 2004, KDD.

[20]  Greg Turk,et al.  Keyframe control of complex particle systems using the adjoint method , 2006, SCA '06.

[21]  Sarah Tariq,et al.  Scalable fluid simulation using anisotropic turbulence particles , 2010, ACM Trans. Graph..

[22]  Adam Finkelstein,et al.  Stylized keyframe animation of fluid simulations , 2014, NPAR '14.

[23]  Dino Pedreschi,et al.  Interactive visual clustering of large collections of trajectories , 2009, 2009 IEEE Symposium on Visual Analytics Science and Technology.

[24]  Ming C. Lin,et al.  Example-guided physically based modal sound synthesis , 2013, ACM Trans. Graph..

[25]  Eitan Grinspun,et al.  TRACKS: toward directable thin shells , 2007, ACM Trans. Graph..

[26]  Markus H. Gross,et al.  Efficient simulation of example-based materials , 2012, SCA '12.

[27]  Fabrice Neyret,et al.  Advected textures , 2003, SCA '03.

[28]  Anthony K. H. Tung,et al.  Spatial clustering methods in data mining : A survey , 2001 .

[29]  Miguel A. Otaduy,et al.  Animating Wrinkles by Example on Non-Skinned Cloth , 2013, IEEE Transactions on Visualization and Computer Graphics.

[30]  Markus Wacker,et al.  Multilayered Wrinkle Textures from Strain , 2004, VMV.

[31]  Rui Xu,et al.  Survey of clustering algorithms , 2005, IEEE Transactions on Neural Networks.

[32]  Rubaiat Habib Kazi,et al.  Draco: bringing life to illustrations with kinetic textures , 2014, CHI.

[33]  Roman Durikovic,et al.  SPH with small scale details and improved surface reconstruction , 2011, SCC.

[34]  Dino Pedreschi,et al.  Time-focused clustering of trajectories of moving objects , 2006, Journal of Intelligent Information Systems.

[35]  Alla Sheffer,et al.  Animation wrinkling: augmenting coarse cloth simulations with realistic-looking wrinkles , 2010, ACM Trans. Graph..

[36]  H. Seidel,et al.  Pattern-aware Deformation Using Sliding Dockers , 2011, SIGGRAPH 2011.

[37]  Eli Shechtman,et al.  LazyFluids: appearance transfer for fluid animations , 2015, ACM Trans. Graph..

[38]  Robert Bridson,et al.  Evolving sub-grid turbulence for smoke animation , 2008, SCA '08.

[39]  Matthias Müller,et al.  Real-time simulation of large bodies of water with small scale details , 2010, SCA '10.

[40]  Matthias Teschner,et al.  Unified spray, foam and air bubbles for particle-based fluids , 2012, The Visual Computer.

[41]  Li-Yi Wei,et al.  Discrete element textures , 2011, ACM Trans. Graph..

[42]  Ulrich Rüde,et al.  Detail-preserving fluid control , 2006, Symposium on Computer Animation.

[43]  Sylvain Lefebvre,et al.  Dynamic element textures , 2013, ACM Trans. Graph..