Title

Event probability mask (EPM) and event denoising convolutional neural network (EDNCNN) for neuromorphic cameras

Document Type

Conference Paper

Publication Date

1-1-2020

Publication Source

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Abstract

This paper presents a novel method for labeling real-world neuromorphic camera sensor data by calculating the likelihood of generating an event at each pixel within a short time window, which we refer to as “event probability mask” or EPM. Its applications include (i) objective benchmarking of event denoising performance, (ii) training convolutional neural networks for noise removal called “event denoising convolutional neural network” (EDnCNN), and (iii) estimating internal neuromorphic camera parameters. We provide the first dataset (DVSNOISE20) of real-world labeled neuromorphic camera events for noise removal.

Inclusive pages

1698-1707

ISBN/ISSN

1063-6919

Publisher

IEEE


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