An algorithmic model of heading perception

Abstract.On the basis of Hanada and Ejima’s (2000) model, an algorithmic model was presented to explain psychophysical data of van den Berg and Beintema (2000) that are inconsistent with vector-subtractive compensation for the rotational flow. The earlier model was modified in order not to use vector-subtractive compensation for the rotational flow. The proposed model computes the center of flow first and then estimates self-rotation; finally, heading is recovered from the center of flow and the estimate of self-rotation. The model explains the data of van de Berg and Beintema (2000). A fusion model of rotation estimates from different sources (efferent signals, proprioceptive feedback, vestibular signals about eye and head rotation, and visual motion) was also presented.

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