We present a biologically-inspired model for the one-shot vergence control of a robotic head, which has been used for an investigation of two vergence control networks. Both networks do not work with explicitly computed disparity, but extract the vergence control signal from the postprocessed response of a population of disparity tuned complex cells, the actual gaze direction and the actual vergence angle. Training and evaluation of the networks are also discussed. ©2009 IEEE.
Convolutional network for vergence control / Chumerin, N.; Gibaldi, A.; Sabatini, S. P.; Van Hulle, M. M.. - (2009), pp. 1-6. (Intervento presentato al convegno 2nd International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL 2009 tenutosi a Bratislava, svk nel NOV 24-27, 2009) [10.1109/ISABEL.2009.5373674].
Convolutional network for vergence control
Gibaldi A.;
2009
Abstract
We present a biologically-inspired model for the one-shot vergence control of a robotic head, which has been used for an investigation of two vergence control networks. Both networks do not work with explicitly computed disparity, but extract the vergence control signal from the postprocessed response of a population of disparity tuned complex cells, the actual gaze direction and the actual vergence angle. Training and evaluation of the networks are also discussed. ©2009 IEEE.
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