Collision‐Aware and Online Compression of Rigid Body Simulations via Integrated Error Minimization

Methods to compress simulation data are invaluable as they facilitate efficient transmission along the visual effects pipeline, fast and efficient replay of simulations for visualization and enable storage of scientific data. However, all current approaches to compressing simulation data require access to the entire dynamic simulation, leading to large memory requirements and additional computational burden. In this paper we perform compression of contact‐dominated, rigid body simulations in an online, error‐bounded fashion. This has the advantage of requiring access to only a narrow window of simulation data at a time while still achieving good agreement with the original simulation. Our approach is simulator agnostic allowing us to compress data from a variety of sources. We demonstrate the efficacy of our algorithm by compressing contact‐dominated rigid body simulations from a number of sources, achieving compression rates of up to 360 times over raw data size.

[1]  Voicu Popescu,et al.  Simplification of Node Position Data ;for Interactive Visualization of Dynamic Data Sets , 2012, IEEE Transactions on Visualization and Computer Graphics.

[2]  Jane McGonigal,et al.  Keynote: Jane McGonigal , 2012, ACM Transactions on Graphics.

[3]  Jarek Rossignac,et al.  Dynapack: space-time compression of the 3D animations of triangle meshes with fixed connectivity , 2003, SCA '03.

[4]  Yaser Sheikh,et al.  Bilinear spatiotemporal basis models , 2012, TOGS.

[5]  Shixiong Xia,et al.  An Overview of Moving Object Trajectory Compression Algorithms , 2016 .

[6]  Hans-Peter Seidel,et al.  Animating deformable objects using sparse spacetime constraints , 2014, ACM Trans. Graph..

[7]  Nicolas Courty,et al.  Motion Compression using Principal Geodesics Analysis , 2009, Comput. Graph. Forum.

[8]  Terry A. Welch,et al.  A Technique for High-Performance Data Compression , 1984, Computer.

[9]  Alec Jacobson,et al.  Skinning: real-time shape deformation , 2014, SIGGRAPH ASIA Courses.

[10]  Ken Museth,et al.  Hierarchical RLE level set: A compact and versatile deformable surface representation , 2006, TOGS.

[11]  Theodore Kim,et al.  Compressing fluid subspaces , 2016, Symposium on Computer Animation.

[12]  Guodong Liu,et al.  Segment-based human motion compression , 2006, SCA '06.

[13]  Doug L. James,et al.  Skinning mesh animations , 2005, ACM Trans. Graph..

[14]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .

[15]  Marc Alexa,et al.  Representing Animations by Principal Components , 2000, Comput. Graph. Forum.

[16]  Libor Vása,et al.  Compressing dynamic meshes with geometric laplacians , 2014, Comput. Graph. Forum.

[17]  Ken Shoemake,et al.  Animating rotation with quaternion curves , 1985, SIGGRAPH.

[18]  Céline Hudelot,et al.  3D Mesh Compression , 2015, ACM Comput. Surv..

[19]  Urs Ramer,et al.  An iterative procedure for the polygonal approximation of plane curves , 1972, Comput. Graph. Image Process..

[20]  Erwin Coumans,et al.  Bullet physics simulation , 2015, SIGGRAPH Courses.

[21]  Craig Gotsman,et al.  Compression of soft-body animation sequences , 2004, Comput. Graph..

[22]  Stefan Jeschke,et al.  Long range constraints for rigid body simulations , 2017, Symposium on Computer Animation.

[23]  Jeremy Schofield,et al.  Efficient algorithms for rigid body integration using optimized splitting methods and exact free rotational motion. , 2008, The Journal of chemical physics.

[24]  Peter Schröder,et al.  Smoke rings from smoke , 2014, ACM Trans. Graph..

[25]  Ralf Sarlette,et al.  Simple and efficient compression of animation sequences , 2005, SCA '05.

[26]  H. Rein,et al.  REBOUND: An open-source multi-purpose N-body code for collisional dynamics , 2011, 1110.4876.

[27]  Ramses van Zon,et al.  Numerical implementation of the exact dynamics of free rigid bodies , 2006, J. Comput. Phys..

[28]  Maarten van Someren,et al.  Clustering Vessel Trajectories with Alignment Kernels under Trajectory Compression , 2010, ECML/PKDD.

[29]  Doug L. James,et al.  Many-worlds browsing for control of multibody dynamics , 2007, SIGGRAPH 2007.

[30]  David Goodhue.  Velocity-based compression of 3D animated rotations , 2017, SIGGRAPH Posters.

[31]  Françoise J. Prêteux,et al.  Optimized MPEG-4 animation encoder for motion capture data , 2007, Web3D '07.

[32]  Eitan Grinspun,et al.  Reflections on simultaneous impact , 2012, ACM Trans. Graph..

[33]  Okan Arikan.  Compression of motion capture databases , 2006, ACM Trans. Graph..

[34]  Eitan Grinspun,et al.  All's well that ends well , 2017, ACM Trans. Graph..

[35]  Doug L. James,et al.  Skinning mesh animations , 2005, SIGGRAPH 2005.

[36]  Ulrich Pinkall,et al.  Hierarchical vorticity skeletons , 2017, Symposium on Computer Animation.

[37]  Benjamin Keinert,et al.  Spherical fibonacci mapping , 2015, ACM Trans. Graph..