An Analysis of the Motion Signal Distributions Emerging from Locomotion through a Natural Environment

Some 50 years have passed since Gibson drew attention to the characteristic field of velocity vectors generated on the retina when an observer is moving through the three-dimensional world. Many theoretical, psychophysical, and physiological studies have demonstrated the use of such optic flow-fields for a number of navigational tasks under laboratory conditions, but little is known about the actual flowfield structure under natural operating conditions. To study the motion information available to the visual system in the real world, we moved a panoramic imaging device outdoors on accurately defined paths and simulated a biologically inspired motion detector network to analyse the distribution of motion signals. We found that motion signals are sparsely distributed in space and that local directions can be ambiguous and noisy. Spatial or temporal integration would be required to retrieve reliable information on the local motion vectors. Nevertheless, a surprisingly simple algorithm can retrieve rather accurately the direction of heading from sparse and noisy motion signal maps without the need for such pooling. Our approach thus may help to assess the role of specific environmental and computational constraints in natural optic flow processing.