Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/20.500.12104/66448
Título: Neurofuzzy prediction for gaze control
Autor: Cuevas, E.
Zaldivar, D.
Rojas, R.
Fecha de titulación: 2009
Resumen: Real-time gaze control is a complicated task because of the different dynamics of the elements involved in the process. On the one hand, the algorithms for image processing are usually very time-consuming. On the other hand, the motors and mechanisms used to control camera movements are very slow. This work describes the use of an adaptive network-based fuzzy inference system (ANFIS) model to reduce the delay effects in gaze control and also explains how the delay problem is resolved through prediction of the target movement using a neurofuzzy approach. The approach has been successfully tested in the vision system of a humanoid robot. The predictions improve the velocity and accuracy of object tracking. © 2005 IEEE.
URI: http://hdl.handle.net/20.500.12104/66448
Aparece en las colecciones:Producción científica UdeG (prueba)

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