title: Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform.
abstract: Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks.
authors.affiliation: Department Technology and Health, Istituto Superiore di Sanità Rome, Italy.
authors.forename: Massimiliano
authors.initials: M
authors.lastname: Giulioni
authors.affiliation: Vision and Natural Computation Group, Institut National de la Santé et de la Recherche MédicaleParis, France; Sorbonne Universités, Institut de la Vision, Université de Paris 06 Pierre et Marie Curie, Centre National de la Recherche ScientifiqueParis, France.
authors.forename: Xavier
authors.initials: X
authors.lastname: Lagorce
authors.affiliation: Vision and Natural Computation Group, Institut National de la Santé et de la Recherche MédicaleParis, France; Sorbonne Universités, Institut de la Vision, Université de Paris 06 Pierre et Marie Curie, Centre National de la Recherche ScientifiqueParis, France.
authors.forename: Francesco
authors.initials: F
authors.lastname: Galluppi
authors.affiliation: Vision and Natural Computation Group, Institut National de la Santé et de la Recherche MédicaleParis, France; Sorbonne Universités, Institut de la Vision, Université de Paris 06 Pierre et Marie Curie, Centre National de la Recherche ScientifiqueParis, France.
authors.forename: Ryad B
authors.initials: RB
authors.lastname: Benosman
keywords: analog VLSI; motion-flow; silicon retina; spike-based