Adaptive Sampling of Motion Trajectories for Discrete Task-bases Analysis and Synthesis of Gesture

Pierre-François Marteau (1) , Sylvie Gibet (1)

1 EXPRESSION - Expressiveness in Human Centered Data/Media

This paper addresses the problem of synthesizing in real time the motion of realistic virtual characters with a physics-based model from the analysis of human motion data. The synthesis is achieved by computing the motion equations of a dynamical model controlled by a sensory motor feedback loop with a non-parametric learning approach. The analysis is directly applied on end-effector trajectories captured from human motion. We have developed a Dynamic Programming Piecewise Linear Approximation model (DPPLA) that generates the discretization of these 3D Cartesian trajectories. The DPPLA algorithm leads to the identification of discrete target-patterns that constitute an adaptive sampling of the initial end-point trajectory. These sequences of samples non uniformly distributed along the trajectory are used as input of our sensory motor system. The synthesis of motion is illustrated on a dynamical model of a hand-arm system, each arm being represented by seven degrees of freedom. We show that the algorithm works on multi-dimensional variables and reduces the information flow at the command level with a good compression rate, thus providing a technique for motion data in- dexing and retrieval. Furthermore, the adaptive sampling seems to be correlated with some invariant law of human motion.

Domaines: Informatique

Pierre-François Marteau, Sylvie Gibet. Adaptive Sampling of Motion Trajectories for Discrete Task-bases Analysis and Synthesis of Gesture. Sylvie Gibet; Nicolas Courty; Jean-François Kamp. Gesture in Human-Computer Interaction and Simulation, 6th International Gesture Workshop, Lecture Notes in Computer Science (3881), Springer-Verlag Berlin Heidelberg, pp.224 - 235, 2006, GW 2005, 978-3-540-32624-3. ⟨hal-01367901⟩