Super-Resolution Spike Event-based Polarimetric Dynamic Vision Sensor p(DVS) Cognitive Imaging

Anthony Beninati, Martin Nowak, Nicolas Douard, Joe Lanzi, Ridwan Hussain, Yi Wang, S. Shrestha, Zoe Giakos, G. Giakos
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Abstract

In this study, a novel experimental design of a cognitive imaging system aiming at enhancing the spatial and temporal resolution of neuromorphic vision sensors, is presented. Super resolution images of moving or semi-obstructed targets, by means of the “Polarimetric Dynamic Vision Sensor (pDVS)” system, were obtained. This system improves the contrast sensitivity and proves to be an efficient strategy for rapid scene analysis by making use of deep learning. The outcome of this study has a tremendous impact to contribute to the design of innovative bioinspired-based vision systems for rapid classification, identification, motion detection, and tracking.
超分辨率脉冲事件极化动态视觉传感器认知成像
本研究提出了一种新的认知成像系统的实验设计,旨在提高神经形态视觉传感器的空间和时间分辨率。利用“偏振动态视觉传感器”系统,获得了运动或半遮挡目标的超分辨率图像。该系统利用深度学习提高了对比灵敏度,是一种快速场景分析的有效策略。这项研究的结果对设计创新的基于生物灵感的视觉系统具有巨大的影响,用于快速分类、识别、运动检测和跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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