Understanding visuomotor coordination requires the study of tasks that engage mechanisms for the integration of visual and motor information; in this paper we choose a paradigmatic yet little studied example of such a task, namely realistic drawing. On the one hand, our data indicate that the motor task has little influence on which regions of the image are overall most likely to be fixated: salient features are fixated most often. Viceversa, the effect of motor constraints is revealed in the temporal aspect of the scanpaths: 1) sub jects direct their gaze to an ob ject mostly when they are acting upon (drawing) it; and 2) in suport of graphically continuous hand movements, scanpaths resemble edge–following patterns along image contours. For a better understanding of such properties, a computational model is proposed in the form of a novel kind of Dynamic Bayesian Network, and simulation results are compared with human eye–hand data.
Visuomotor Characterization of Eye Movements in a Drawing Task / R. Coen-Cagli, P. Coraggio, P. Napoletano, O. Schwartz, M. Ferraro, G. Boccignone. - In: VISION RESEARCH. - ISSN 0042-6989. - 49:8(2009 May 04), pp. 810-818. [10.1016/j.visres.2009.02.016]
Visuomotor Characterization of Eye Movements in a Drawing Task
G. BoccignoneUltimo
2009
Abstract
Understanding visuomotor coordination requires the study of tasks that engage mechanisms for the integration of visual and motor information; in this paper we choose a paradigmatic yet little studied example of such a task, namely realistic drawing. On the one hand, our data indicate that the motor task has little influence on which regions of the image are overall most likely to be fixated: salient features are fixated most often. Viceversa, the effect of motor constraints is revealed in the temporal aspect of the scanpaths: 1) sub jects direct their gaze to an ob ject mostly when they are acting upon (drawing) it; and 2) in suport of graphically continuous hand movements, scanpaths resemble edge–following patterns along image contours. For a better understanding of such properties, a computational model is proposed in the form of a novel kind of Dynamic Bayesian Network, and simulation results are compared with human eye–hand data.File | Dimensione | Formato | |
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