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.

What the draughtman's hand tells the draughtman's eye : a sensorimotor account of drawing / R. COEN CAGLI, P. CORAGGIO, P. NAPOLETANO, G. BOCCIGNONE. - In: INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE. - ISSN 0218-0014. - 22:5(2008 Aug), pp. 1015-1029. [10.1142/S021800140800665X]

What the draughtman's hand tells the draughtman's eye : a sensorimotor account of drawing

G. Boccignone
Ultimo
2008

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.
Active vision; Biologically-inspired robots; Dynamic Bayesian networks; Sensorimotor integration
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/53352
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