foveation

Foveation is a concept borrowed from visual perception and applied to image processing and computer vision. In human vision, the fovea is a small pit in the retina responsible for sharp central vision. When we look at something, our eyes rapidly move, or saccade, to bring the object of interest into the fovea, allowing for detailed perception.

In computer vision, foveation simulates this biological process. It refers to a technique where an image is processed with varying degrees of resolution. The central region of interest, analogous to the fovea, is rendered at a high resolution, while the peripheral areas are rendered at progressively lower resolutions. This is often achieved by using a "foveal" or "gaze" point, which indicates the current focus of attention.

The primary benefit of foveation in computer vision is computational efficiency. By dedicating more processing power to the area of interest and less to the periphery, the overall computational load can be significantly reduced. This is particularly useful in real-time applications such as autonomous driving, video surveillance, and virtual reality where rapid processing is crucial.

Implementing foveation typically involves creating a variable resolution representation of an image. This can be done using techniques like Gaussian pyramids or specific foveated rendering algorithms. The "gaze" point can be determined by user input, object detection algorithms, or other cues that signify where the system should focus its attention. This dynamic adjustment of resolution based on focus makes foveation a powerful tool for optimizing visual processing systems.