Abstract
We have developed a system that can detect a moving object during global motion. The system includes a silicon retina, a field-programmable gate array (FPGA), and a personal computer (PC). The system operates at 200 frames per second. The algorithm and the architecture of our system were inspired by the neuronal network model of the object motion sensitive (OMS) ganglion cells, which respond selectively to an object whose moving timing and velocity are different from those of global motion. In order to simulate the spatial and temporal characteristics of the neural activities of the model effectively, we employed analog-digital hybrid architecture including resistive networks and an FPGA. The output of the system was examined using visual stimuli displayed on a LCD monitor, and the system was successful in extracting the region of a moving object.
