Cortical dynamics of three-dimensional surface perception: binocular and half-occluded scenic images
Transactions of the Society for Computer Simulation International - Special issue: simulation methodology in transportation systems
Recurrent long-range interactions in early vision
Emergent neural computational architectures based on neuroscience
Neural Computation
Towards novel neuroscience-inspired computing
Emergent neural computational architectures based on neuroscience
Neural mechanisms for the robust representation of junctions
Neural Computation
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
A computational approach to illusory contour perception based on the tensor voting technique
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
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Contours and surfaces are basic qualities which are processed by the visual system to aid the successful behavior of autonomous beings within the environment. There is increasing evidence that the two modalities of contours and surfaces are processed in separate, but interacting visual streams or sub-systems. Neurons at early stages in the visual system show strong responses only at locations of high contrast, such as edges, but only weak responses within homogeneous regions. Thus, for the processing and representation of surfaces, the visual system has to integrate sparse local measurements into a dense, coherent representation. We suggest a mechanism of confidence-based filling-in, where a confidence measure ensures a robust selection of sparse contrast signals. The new mechanism supports the generation of surface representations which are invariant against size and shape transformation. The filling-in process is controlled by contour or boundary signals which stop the filling-in of contrast signals at region boundaries. Localized responses to contours are most often noisy and fragmented. We suggest a recurrent processing scheme for the extraction of contours that incorporates long-range connections. The recurrent long-range processing enhances coaligned activity which is consistent within a more global context, while inconsistent noisy activity is suppressed. The capability of the model is shown for noisy synthesized and natural stimuli.