Motion perception at equiluminance and the consequences for computational vision systems

When the image of a moving object is equal in luminance with the background, we observe a startling change in both its apparent motion and its three-dimensional position in space. If we use biological vision as a guide for the construction of machine vision systems, this perceptual phenomenon has profound implications. Motion information can be used in a variety of visual tasks such as detection, calibration, guided movement, navigation, and recognition. Human performance at equiluminance suggests that navigation uses motion information heavily and that for recognition, motion plays only a role such as separating figure from ground or grossly defining surface in space. Equiluminant motion perception cannot tell us much about detection, calibration, or guided movement tasks. We demonstrate an adaptive model of motion perception which presents similar equiluminant responses.