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This paper introduces a framework of gesture recognition operating on theoutput of an event based camera using the computational resources of a mobilephone. We will introduce a new development around the concept of time-surfacesmodified and adapted to run on the limited computational resources of a mobileplatform. We also introduce a new method to remove dynamically backgrounds thatmakes full use of the high temporal resolution of event-based cameras. Weassess the performances of the framework by operating on several dynamicscenarios in uncontrolled lighting conditions indoors and outdoors. We alsointroduce a new publicly available event-based dataset for gesture recognitionselected through a clinical process to allow human-machine interactions for thevisually-impaired and the elderly. We finally report comparisons with priorworks that tackled event-based gesture recognition reporting comparable if notsuperior results if taking into account the limited computational and memoryconstraints of the used hardware.

Event-based Gesture Recognition with Dynamic Background Suppression using Smartphone Computational Capabilities