A computational model for the control of horizontal vergence, based on a population of disparity tuned complex cells, is presented. The model directly extracts the disparity-vergence response by combining the outputs of the disparity detectors without explicit calculation of the disparity map. The resulting vergence control yields to stable fixation and has small response time to a wide range of disparities. Experimental simulations with synthetic stimuli in depth validated the approach.
A neural model for binocular vergence control without explicit calculation of disparity / Gibaldi, A.; Chessa, M.; Canessa, A.; Sabatini, S. P.; Solari, F.. - (2009), pp. 293-298. (Intervento presentato al convegno 17th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning, ESANN 2009 tenutosi a Bruges, bel nel 2009).
A neural model for binocular vergence control without explicit calculation of disparity
Gibaldi A.;Canessa A.;
2009
Abstract
A computational model for the control of horizontal vergence, based on a population of disparity tuned complex cells, is presented. The model directly extracts the disparity-vergence response by combining the outputs of the disparity detectors without explicit calculation of the disparity map. The resulting vergence control yields to stable fixation and has small response time to a wide range of disparities. Experimental simulations with synthetic stimuli in depth validated the approach.
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