Demetri Terzopoulos gave the opening keynote titled Biomechanical and Artificial Life Simulation of Humans for Computer Animation and Games, after which there were sessions on simulation, animation and GPU techniques.
I hadn’t heard before, but Demetri’s group recently released this ambitious paper: Comprehensive Biomechanical Modeling and Simulation of the Upper Body
Some particularly cool papers from day 1:
Jonathan Cohen, Sarah Tariq, and Simon Green. Interactive Fluid-Particle Simulation using Translating Eulerian Grids. link
The talk started with some very useful high level observations and motivation. Jonathan emphasized that our goal should be scalable physics, not just fast, realistic physics. Sequential algorithms are insufficient. Parallel algorithms alone are also insufficient. We want parallel algorithms that produce better looking results as hardware gets better. There were some cool ideas here: Use Gallilean invariance to replace translations of the simulation grid with fluctuating boundary conditions (modeling the entrance/exit of matter from the volume). Apply the fluid simulation to particles with less influence as you move towards the edge of the grid. This gets around the simulation/fluid in a box problem. Cool tidbit: They used this technique for jetpacks and one of the guns in the videogame Dark Void.
Christian Miller, Okan Arikan and Donald Fussell. Frankenrigs: Building Character Rigs From Multiple Sources. link
(Full disclosure: I know all of the authors fairly well from my time at UT Austin.) This is an end-to-end system for (semi-)automatically rigging and skinning character meshes. I didn’t know this, but rigging and skinning is tedious for experts and nearly impossible for everyone else. The idea was to take a data-driven approach and leverage previously skinned and rigged character meshes (of which game and movie studios have plenty lying around). The input meshes are cut into limbs and then appropriate limbs are matched to the target mesh and stitched together. Hence the name: Frankenrigs. One very interesting observation: The method handles non-manifold, non-closed meshes, which is the way almost all artists’ meshes come. Christian actually ran into this problem when comparing to previous work: He couldn’t because the past work didn’t work on non-closed meshes.
Samuli Laine and Tero Karras. Efficient Sparse Voxel Octrees. link
This paper had a really killer demo. They managed to voxelize and render at reasonably high fidelity the NVIDIA street scene and the Sibenik cathedral scene. Along with the Gigavoxels paper, this makes it look like adaptive resolution voxel grids may be gaining a lot of traction. The contributions here were mainly an efficient ray marching algorithm, and effectively handling and filtering normals. The authors have open sourced the code base, so if you’re looking to get your hands dirty with some voxel rendering and/or research, this might be a good place to start.