Asynchronous frameless event-based optical flow

Authors:
Ryad Benosman;Sio-Hoi Ieng;Charles Clercq;Chiara Bartolozzi;Mandyam Srinivasan
Affiliations:
Vision Institute, University Pierre and Marie Curie-UPMC/CNRS UMR7222, Paris, France;Vision Institute, University Pierre and Marie Curie-UPMC/CNRS UMR7222, Paris, France;Italian Institute of Technology, Genova, Italy;Italian Institute of Technology, Genova, Italy;University of Queensland at the Queensland Brain Institute, Australia
Venue:
Neural Networks
Year:
2012

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Abstract

This paper introduces a process to compute optical flow using an asynchronous event-based retina at high speed and low computational load. A new generation of artificial vision sensors has now started to rely on biologically inspired designs for light acquisition. 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 for processing visual data using asynchronous event-based acquisition, providing a method for the evaluation of optical flow. The paper shows that current limitations of optical flow computation can be overcome by using event-based visual acquisition, where high data sparseness and high temporal resolution permit the computation of optical flow with micro-second accuracy and at very low computational cost.