Bio-inspired Motion Estimation with Event-Driven Sensors

Abstract

This paper presents a method for image motion estimation for event-based sensors. Accurate and fast image flow estimation still challenges Computer Vision. A new paradigm based on asynchronous event-based data provides an interesting alternative and has shown to provide good estimation at high contrast contours by estimating motion based on very accurate timing. However, these techniques still fail in regions of high-frequency texture. This work presents a simple method for locating those regions, and a novel phase-based method for event sensors that estimates more accurately these regions. Finally, we evaluate and compare our results with other state-of-the-art techniques

Publication
In International Work-Conference on Artificial Neural Networks
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Francisco Barranco
Francisco Barranco
Associate Professor of Computer Engineering

Neuromorph, Hardware, CPS, Graná, Tellurider, UMD & DC.

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