In our daily life, we move in the environment, grab objects and perform a number of actions that are fundamental to our survival. These actions may seem very natural and effortless despite the fact that the brain performs an extremely complex analysis of the light pattern that falls on our eyes in order to determine the structure and shape of the surrounding objects. This problem is very difficult to solve since objects are three-dimensional but our eyes only register their two-dimensional projection (also called retinal image), like the film in a camera.

Most vision scientists have approached this problem by asking the following question: How does the brain derive the 3D structure of objects from the information that is present in a certain instant of time in a certain region of the retinal image? Because the image on the retina is two-dimensional and time can be added as a third dimension, the visual stimulation can be represented in a three-dimensional space. The research conducted so far has focused on the problem of how local regions of this space-time domain are analyzed by the visual system, while the problem of how the visual system is capable of integrating the information contained in different spatial-temporal regions has been neglected.

The overall objective of the present research project is to investigate the spatial-temporal integration of information in the recovery of 3D shape from retinal projections. In particular, three goals will be pursued. First, the research will investigate in which manner local visual processing is affected by interactions with stimulus information present in different space-time locations. Second, the research will exploit the stimulus conditions that are responsible for spatial and temporal organization. Third, the research will determine whether spatial and temporal interactions occur among different sources of depth information. Understanding how the human visual system solves this problem will not only be a valuable advance in the study of visual perception but could also produce novel insights toward the building of machines that mimic our behavior and interactions.
 

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