Joint Constraint Modelling Using Evolved Topology Generalized Multi-Layer Perceptron(GMLP)

The accurate simulation of anatomical joint models is important for both medical diagnosis and realistic animation applications.  Quaternion algebra has been increasingly applied to model rotations providing a compact representation while avoiding singularities.  This paper describes the application of artificial neural networks topologically evolved using genetic algorithms to model joint constraints directly in quaternion space.  These networks are trained (using resilient back propagation) to model discontinuous vector fields that act as corrective functions ensuring invalid joint configurations are accurately corrected.  The results show that complex quaternion-based joint constraints can be learned without resorting to reduced coordinate models or iterative techniques used in other quaternion based joint constraint approaches

Principal Geodesic Dynamics

International audienceThis paper presents a new integration of a data-driven approach using dimension reduction and a physically-based simulation for real-time character animation. We exploit Lie group statistical analysis techniques (Principal Geodesic Analysis, PGA) to approximate the pose manifold of a motion capture sequence by a reduced set of pose geodesics. We integrate this kinematic parametrization into a physically-based animation approach of virtual characters, by using the PGA-reduced parametrization directly as generalized coordinates of a Lagrangian formulation of mechanics. In order to achieve real-time without sacrificing stability, we derive an explicit time integrator by approximating existing variational integrators. Finally, we test our approach in task-space motion control. By formulating both physical simulation and inverse kinematics time stepping schemes as two quadratic programs, we propose a features-based control algorithm that interpolates between the two metrics. This allows for an intuitive trade-off between realistic physical simulation and controllable kinematic manipulation