Siggraph 2007 is around the corner, and that means new technology for game developers to play with! In terms of game AI, the most interesting part of the conference is character animation, as it promises to deliver realistic motion for lower investments.
One paper from University of Washington Animation Research Labs presents an active learning controller. There are two innovations here:
A kinematic character controller that can be built incrementally from motion-capture data.
An interactive workflow with the animator for easily adding new motion clips.
This combination makes it easier to build low-level animation behaviors, and visualize them immediately. It reduces turn-around times, and allows the animator to identify problems and correct them with new motion clips.
View or download the movie (MOV, 116 Mb).
Here’s the abstract:
This paper describes an approach to building real-time highly-controllable characters. A kinematic character controller is built on-the-fly during a capture session, and updated after each new motion clip is acquired. Active learning is used to identify which motion sequence the user should perform next, in order to improve the quality and responsiveness of the controller. Because motion clips are selected adaptively, we avoid the difficulty of manually determining which ones to capture, and can build complex controllers from scratch while significantly reducing the number of necessary motion samples.
Download the paper (PDF, 2.4 Mb):
Active Learning for Real-time Motion Controllers Cooper, S. Hertzmann, A. Popovi?, Z. ACM Transactions on Graphics 26(3)
Here’s a quick assessment of the technology based on how easy it would be to use for upcoming games.
- Applicability to games: 6/10
- Only AAA games that rely heavily on mo-cap would benefit. It requires a non-negligible budget for the equipment.
- Usefulness for character AI: 7/10
- Improves animation workflow significantly for human character animations. It provides better and more realistic mo-cap based behaviors.
- Simplicity to implement: 1/10
- The biggest hurdle is the motion capture equipment and interactive environment. But the technology itself also requires animation programming expertise.
Interactive Motion Capture Session
How do you think this kind of technology can be useful to game AI?