Mario Ferraro

Visuomotor Characterization of Eye Movements in a Drawing Task

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) subjects direct their gaze to an object mostly when they are acting upon (drawing) it; and (2) in support 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.

In vitro analysis of neuron-glial cell interactions during cellular migration.

Abstract. We used time-lapse microscopy to study the in vitro migration of neuronal cells from developing chick ciliary ganglion. These cells, when dissociated and cultured in a chemically defined medium, are able to migrate and to associate into clusters. We focused our attention on the study of the distribution of neuronal velocity components. Quantitative analysis of cell trajectories allowed us to demonstrate that, in many cells, velocities are well described by the Langevin equation, when deterministic components of the forces acting on the cells are taken into account. We also have shown that the majority of neurons whose movement is not purely random migrate in association with glial cells. We conclude that glial cells, by guiding neurons during migration, play an important role in the cell organization in vitro.

Lie transformation groups, integral transforms, and invariant pattern recognition

This paper considers image representations based on integral transforms which are invariant under certain transformations, while preserving the uniqueness of the encoding. Necessary and sufficient conditions are determined for the existence of such representations and a method to determine the kernels of the related integral transforms is presented. Finally, the possible relevance of such considerations for the understanding of invariant recognition systems in biological vision is also explored.

Discrete and continuous modes of curved-line discrimination controlled by effective stimulus duration.

In previous experiments two extreme modes of visual discrimination performance have been investigated by measuring small differences in pattern shape at points along a continuum of pattern shapes. These two modes, associated with discrete and continuous encoding processes, were obtained by simultaneously manipulating the number of pattern components in the display and the effective duration of the display. In this experiment, discrimination performance was measured for a fixed number of pattern components, namely three, and variable display time course. The stimuli used were curved lines drawn from a continuum with curvature parameter s. There were three stimulus time courses: (1) 2-s stimulus display, (2) 100-ms stimulus display, and (3) 100-ms stimulus display followed by a post-stimulus mask. Discrimination performance declined smoothly and monotonically with s for (1), but varied non-monotonically with s revealing a central peak for (3). Performance for (2) was intermediate between that for (1) and that for (3). A reduction in effective stimulus duration alone was thus sufficient to cause a transition from continuous to discrete modes of discrimination performance, a result which may be compatible with an explanation of variable discrimination modes based on a method of successive internal approximations of the stimulus.

Ecological Sampling of Gaze Shifts

Visual attention guides our gaze to relevant parts of the viewed scene, yet the moment-to-moment relocation of gaze can be different among observers even though the same locations are taken into account. Surprisingly, the variability of eye movements has been so far overlooked by the great majority of computational models of visual attention. In this paper we present the ecological sampling model, a stochastic model of eye guidance explaining such variability. The gaze shift mechanism is conceived as an active random sampling that the foraging eye carries out upon the visual landscape, under the constraints set by the observable features and the global complexity of the landscape. By drawing on results reported in the foraging literature, the actual gaze relocation is eventually driven by a stochastic differential equation whose noise source is sampled from a mixture of α-stable distributions. This way, the sampling strategy proposed here allows to mimic a fundamental property of the eye guidance mechanism: where we choose to look next at any given moment in time, it is not completely deterministic, but neither is it completely random To show that the model yields gaze shift motor behaviors that exhibit statistics similar to those displayed by human observers, we compare simulation outputs with those obtained from eye-tracked subjects while viewing complex dynamic scenes.

Entropy-based representation of image information

Loss of information in images undergoing fine-to-coarse transformations is analysed by using an approach based on the theory of irreversible processes. In the case of grey level images, entropy variation along scales is used to characterize basic, low-level information and to identify perceptual components of the image, such as shape and texture. Here an extension of the approach to colour images is proposed. Spatio-chromatic information is defined, which depends on cross-interactions between the different colour channels. Examples illustrating the use of spatio-chromatic information are presented, related to pattern recognition and active vision. 2002 Elsevier Science B.V. All rights reserved.

Generalized spatio-chromatic diffusion

A framework for diffusion of color images is presented. The method is based on the theory of thermodynamics of irreversible transformations which provides a suitable basis for designing correlations between the different color channels. More precisely, we derive an equation for color evolution which comprises a purely spatial diffusive term and a nonlinear term that depends on the interactions among color channels over space. We apply the proposed equation to images represented in several color spaces, such as RGB, CIELAB, Opponent colors, and IHS.

Gaussian Mixture Model of Heart Rate Variability

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters.

An information-theoretic approach to active vision

An approach to active vision based on information theory and statistical mechanics is presented. Density of entropy production measured along a spatio-chromatic diffusion of a colour image is used to build a conspicuity map of the image. The map is successively given as input to a dynamic neural network in order to drive a focus-of-attention scanpath.

Image Warping for Shape Recovery and Recognition

We demonstrate that, for a large class of reflectance functions, there is a direct relationship between image warps and the corresponding geometric deformations of the underlying three-dimensional objects. This helps explain the hidden geometrical assumptions in object recognition schemes which involve two-dimensional image warping computed by matching image intensity. In addition, it allows us to propose a novel variant of shape from shading which we call shape from image warping. The idea is that the three-dimensional shape of an object is estimated by determining how much the image of the object is warped with respect to the image of a known prototype shape. Therefore, detecting the image warp relative to a prototype of known shape allows us to reconstruct the shape of the imaged object. We derive properties of these shape warps and illustrate the results by recovering the shapes of faces.