WHAT THE DRAUGHTSMAN'S HAND TELLS THE DRAUGHTSMAN'S EYE: A SENSORIMOTOR ACCOUNT OF DRAWING

Abstract

In this paper we address the challenging problem of sensorimotor integration, with reference to eye-hand coordination of an artificial agent engaged in a natural drawing task. Under the assumption that eye-hand coupling influences observed movements, a motor continuity hypothesis is exploited to account for how gaze shifts are constrained by hand movements. A Bayesian model of such coupling is presented in the form of a novel Dynamic Bayesian Network, namely an Input–Output Coupled Hidden Markov Model. Simulation results are compared to those obtained by eye-tracked human subjects involved in drawing experiments.