Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
Jun Morimoto, Christopher G. Atkeson, Gen Endo, Go...
Abstract. In this work, synthesis of facial animation is done by modelling the mapping between facial motion and speech using the shared Gaussian process latent variable model. Bot...
Most state-of-the-art nonrigid shape recovery methods
usually use explicit deformable mesh models to regularize
surface deformation and constrain the search space. These
triangu...
Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...