Motion texture: a two-level statistical model for character motion synthesis
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Interactive control of avatars animated with human motion data
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Precomputing avatar behavior from human motion data
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Evaluating motion graphs for character navigation
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
Responsive characters from motion fragments
ACM SIGGRAPH 2007 papers
Near-optimal character animation with continuous control
ACM SIGGRAPH 2007 papers
Simulating competitive interactions using singly captured motions
Proceedings of the 2007 ACM symposium on Virtual reality software and technology
Proceedings of the 2007 ACM symposium on Virtual reality software and technology
Interaction patches for multi-character animation
ACM SIGGRAPH Asia 2008 papers
Character animation in two-player adversarial games
ACM Transactions on Graphics (TOG)
Motion fields for interactive character locomotion
ACM SIGGRAPH Asia 2010 papers
Gesture synthesis adapted to speech emphasis
Speech Communication
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We propose a method of generating avoidance motions. We use a motion graph to generate continuous motions, including both avoidance and other kinds of motions. In the combat of real humans, trained fighters avoid an attack with minimal movement. To realize such avoidance motion, we developed criteria to find an appropriate path (series of edges) in the motion graph. The characters are expected to move their body by only a minimal distance to avoid an attack. We introduced attack, body and avoidance space–time volumes to evaluate this criterion. Each candidate path is evaluated according to the distance between attack and body volumes and the overlap between attack and avoidance volumes. We also introduced a method to control the execution speeds of edges, and thus adjust the timing of avoidance motions. Moreover, to find a path in real time, we developed methods to facilitate the searching process such as the use of grid-based indices to look up candidate paths and GPU-based quick collision detection to cull candidate paths. We tested our approach on an application in which a character avoids incoming balls controlled by a user and demonstrated the effectiveness of our approach.