Real-time motion retargeting to highly varied user-created morphologies

被引:101
作者
Hecker, Chris
Raabe, Bernd
Enslow, Ryan W.
DeWeese, John
Maynard, Jordan
van Prooijen, Kees
机构
来源
ACM TRANSACTIONS ON GRAPHICS | 2008年 / 27卷 / 03期
关键词
character animation; motion retargeting; user generated content; inverse kinematics; procedural animation; games;
D O I
10.1145/1360612.1360626
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Character animation in video games-whether manually key-trained or motion captured-has traditionally relied on codifying skeletons early in a game's development, and creating animations rigidly tied to these fixed skeleton morphologies. This paper introduces a novel system for animating characters whose morphologies are unknown at the time the animation is created. Our authoring tool allows animators to describe motion using familiar posing and key-framing methods. The system records the data in a morphology-independent form, preserving both the animation's structural relationships and its stylistic information. At runtime, the generalized data are applied to specific characters to yield pose goals that are supplied to a robust and efficient inverse kinematics solver. This system allows LIS to animate characters with highly varying skeleton morphologies that did not exist when the animation was authored, and, indeed, may be radically different than anything the original animator envisioned.
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页数:11
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