Human free-walking model for a real-time interactive design of gaits
Computer Animation '90
A physically based approach to 2–D shape blending
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Efficient generation of motion transitions using spacetime constraints
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Procedural motion control techniques for interactive animation of human figures
Procedural motion control techniques for interactive animation of human figures
A high-level control mechanism for human locomotion based on parametric frame space interpolation
Proceedings of the Eurographics workshop on Computer animation and simulation '96
Tracking and modifying human motion with dynamic simulation
ACM SIGGRAPH 99 Conference abstracts and applications
Human motion analysis: a review
Computer Vision and Image Understanding
Parametric Hidden Markov Models for Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Real Time Responsive Animation with Personality
IEEE Transactions on Visualization and Computer Graphics
Verbs and Adverbs: Multidimensional Motion Interpolation
IEEE Computer Graphics and Applications
An Efficient Control over Human Running Animation with Extension of Planar Hopper
PG '98 Proceedings of the 6th Pacific Conference on Computer Graphics and Applications
Separating Style and Content with Bilinear Models
Neural Computation
Synchronization for dynamic blending of motions
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
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Consistent transition algorithms preserve salient source motion features by establishing feature-based correspondence between motions and accordingly warping them before interpolation. These processes are commonly dubbed as preprocessing in motion transition literature. Current transition methods suffer from a lack of economical and generic preprocessing algorithms. Classical computer vision methods for human motion classification and correspondence are too computationally intensive for computer animation. This paper proposes an analytical framework that combines low-level kinematics analysis and high-level knowledge-based analysis to create states that provide coherent snapshots of body-parts active during the motion. These states are then corresponded via a globally optimal search tree algorithm. The framework proposed here is intuitive, controllable, and delivers results in near real-time. The validity and performance of the proposed system are tangibly proven with extensive experiments.