Authors:
Daniele Re
1
;
Agostino Gibaldi
1
;
Silvio P. Sabatini
1
and
Michael W. Spratling
2
Affiliations:
1
University of Genoa, Italy
;
2
King's College London, United Kingdom
Keyword(s):
Disparity, Binocular Vision, Stereopsis, Vergence, Saccade, Attention, Basis Function Networks, Neural Networks, Sensory-sensory Transformations, Sensory-motor Control, Learning, V1 Area, Receptive Field Learning.
Related
Ontology
Subjects/Areas/Topics:
Active and Robot Vision
;
Computer Vision, Visualization and Computer Graphics
;
Early and Biologically-Inspired Vision
;
Image and Video Analysis
;
Motion, Tracking and Stereo Vision
;
Stereo Vision and Structure from Motion
;
Visual Attention and Image Saliency
Abstract:
The human visual system uses saccadic and vergence eyes movements to foveate interesting objects with both eyes, and thus exploring the visual scene. To mimic this biological behavior in active vision, we proposed a bio-inspired integrated system able to learn a functional sensory representation of the environment, together with the motor commands for binocular eye coordination, directly by interacting with the environment itself. The proposed architecture, rather than sequentially combining different functionalities, is a robust integration of different modules that rely on a front-end of learned binocular receptive fields to specialize on different sub-tasks. The resulting modular architecture is able to detect salient targets in the scene and perform precise binocular saccadic and vergence movement on it. The performances of the proposed approach has been tested on the iCub Simulator, providing a quantitative evaluation of the computational potentiality of the learned sensory and
motor resources.
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