title: Detecting moving objects in an optic flow field using direction- and speed-tuned operators.
abstract: An observer moving through a scene must be able to identify moving objects. Psychophysical results have shown that people can identify moving objects based on the speed or direction of their movement relative to the optic flow field generated by the observer's motion. Here we show that a model that uses speed- and direction-tuned units, whose responses are based on the response properties of cells in the primate visual cortex, can successfully identify the borders of moving objects in a scene through which an observer is moving.
authors.affiliation: Department of Mathematics and Computer Science, College of the Holy Cross, United States. Electronic address: croyden@cs.holycross.edu.
authors.forename: Constance S
authors.initials: CS
authors.lastname: Royden
authors.affiliation: Department of Mathematics and Computer Science, College of the Holy Cross, United States.
authors.forename: Michael A
authors.initials: MA
authors.lastname: Holloway
mesh_terms: D006801:Humans; D008962:Models, Theoretical; D009039:Motion Perception / Q000502:physiology*; D011601:Psychophysics; D013028:Space Perception; D014794:Visual Fields / Q000502:physiology*
keywords: Heading; Modeling; Motion; Moving object detection; Optic flow