title: Event-based visual flow.
abstract: This paper introduces a new methodology to compute dense visual flow using the precise timings of spikes from an asynchronous event-based retina. Biological retinas, and their artificial counterparts, are totally asynchronous and data-driven and rely on a paradigm of light acquisition radically different from most of the currently used frame-grabber technologies. This paper introduces a framework to estimate visual flow from the local properties of events' spatiotemporal space. We will show that precise visual flow orientation and amplitude can be estimated using a local differential approach on the surface defined by coactive events. Experimental results are presented; they show the method adequacy with high data sparseness and temporal resolution of event-based acquisition that allows the computation of motion flow with microsecond accuracy and at very low computational cost.
authors.forename: Ryad
authors.initials: R
authors.lastname: Benosman
authors.forename: Charles
authors.initials: C
authors.lastname: Clercq
authors.forename: Xavier
authors.initials: X
authors.lastname: Lagorce
authors.forename: Sio-Hoi
authors.initials: SH
authors.lastname: Ieng
authors.forename: Chiara
authors.initials: C
authors.lastname: Bartolozzi
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D008959:Models, Neurological; D009038:Motion; D057849:Optic Flow / Q000502:physiology*; D012160:Retina / Q000502:physiology; D014795:Visual Pathways / Q000502:physiology*