This week’s Thursday Theory post kicks off a series of white paper reviews from the Symposium on Interactive 3D Games and Graphics 2007, specifically relating to character animation. If you missed it, you can also see AiGameDev.com’s Siggraph 07 coverage from a game AI perspective.
This first submission is from the University of Wisconsin-Madison and introduces techniques for motion graph with parameterized states. There are two major contributions in this paper:
Combining parametric motions (e.g., a blend of multiple walking animations) with a motion graph (i.e. connections to other motions like running).
A method for creating realistic transitions automatically between parametric motions using sampling.
The resulting technology is capable of generating continuous motion that looks realistic, yet is responsive to interactive control of the parameters and type of motion.
View or download the movie (WMV, 30 Mb).
Here’s the abstract:
In this paper, we present an example-based motion synthesis technique that generates continuous streams of high-fidelity, controllable motion for interactive applications, such as video games. Our method uses a new data structure called a parametric motion graph to describe valid ways of generating linear blend transitions between motion clips dynamically generated through parametric synthesis in realtime. Our system specifically uses blending-based parametric synthesis to accurately generate any motion clip from an entire space of motions by blending together examples from that space.
The key to our technique is using sampling methods to identify and represent good transitions between these spaces of motion parameterized by a continuously valued parameter. This approach allows parametric motion graphs to be constructed with little user effort. Because parametric motion graphs organize all motions of a particular type, such as reaching to different locations on a shelf, using a single, parameterized graph node, they are highly structured, facilitating fast decision-making for interactive character control. We have successfully created interactive characters that perform sequences of requested actions, such as cartwheeling or punching.
Download the paper from the site (PDF, 0.3 Mb):
Parametric Motion Graphs Heck, Rachel and Gleicher, Michael. Proceedings of Symposium on Interactive 3D Graphics and Games 2007
Now for a short assessment of the technology based on how simple it would be to use in games.
- Applicability to games: 8/10
- As a heavily mocap based solution, this solution is ideal for AAA studios. (Rachel and Micheal have worked with many companies, including EA and Rockstar.) The technology works with hand-created animations too, but it isn’t as easy to justify the technological investment in this case.
- Usefulness for character AI: 9/10
- Having a logical representation like a motion graph for specifying types of motion, and being able to control each of them with simple parameters is practically perfect — and it almost deserves a ten!
- Simplicity to implement: 8/10
- The sampling algorithms is this paper seem rather simple to implement: just play the animation and gather data to build the transitions. However, there are a few technological dependencies that will take more time, notably building parametric motions automatically (e.g. with correct alignment and synchronization among the different walk cycles).
Directing motion on a screen with a controller.
How do you think this kind of technology can be useful for game AI?