Design and Build of an Anthropomorphic Active Vision System

Abstract

The aim of this thesis project is to design an anthropomorphic active vision system which builds on biomimicry of the human visual system. The proposed system has some of the characteristics associated with such a visual system, such as degrees of freedom associated with movements of the eyes in addition to foveation and vergence capacities associated with human vision. Through this thesis, novel approaches are proposed in regard to specific elements of system design and system testing. Novel approaches have been proposed regarding foveation and vergence relating to system design and use of Inertial Measurement Unit (IMU) devices incorporating Kalman filters relating to testing of the prototyped device. For foveation, integration of fast Deep Convolutional Neural Networks (DCNN) has been proposed. For vergence, a variation of Cross-correlation has been used. This method has the benefit of being computationally inexpensive which is beneficial for real-time operations of the proposed system.