By mimicking human visual processing, TACO Project researchers work to increase the speed by which robotic systems interpret images and recognize objects.
By James E. Gaskin
September 28, 2010
In the human eye, the fovea centralis provides sharp central vision by packing in a high concentration of cone photoreceptors and connecting about half the nerve fibers from the optic nerve onto those cones. This gives high definition to the center 2 percent of the visual field, providing detailed vision and allowing us to read and track clearly the most important objects in the visual field.
TACO, a mangled acronym squeezed from Three-dimensional Adaptive Camera with Object Detection and Foveation, is a European research project applying high-definition 3D vision of a small centralized area to enhance robot vision. The TACO camera will emulate the human eye to increase the resolution of a small central area of the viewing field, refining the focus area to important objects, speeding recognition time and visual processing speeds with a three to 10 times increase in spatial recognition and frame rate. Advances in robust yet low-cost hardware, and the software necessary to rapidly detect objects in the environment, drive the project that started in February 2010 and will run three years.
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