A model of human heading judgement in forward motion

We developed a new computational model of human heading judgement from reti nal flow. The model uses two assumptions: a large number of sampling points in the flow field and a symmetric sampling region around the origin. The a lgorithm estimates self-rotation parameters by calculating statistics whose expectations correspond to the rotation parameters. After the rotational c omponents are removed from the retinal flow, the heading direction is recov ered from the flow field. Performance of the model was compared with human data in three psychophysical experiments. In the first experiment, we gener ated stimuli which simulated self-motion toward the ground, a cloud or a fr ontoparallel plane and found that the simulation results of the model were consistent with human performance. In the second and third experiment, we m easured the slope of the perceived versus simulated heading function when a perturbation velocity weighted according to the distance relative to the f ixation distance was added to the vertical velocity component under the clo ud condition. It was found that as the magnitude of the perturbation was in creased, the slope of the function increased. The characteristics observed in the experiments can be explained well by the proposed model. (C) 2000 El sevier Science Ltd. All rights reserved.