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Neuromorphic Fringe Projection Profilometry

Ashish Rao Mangalore, Chandra Sekhar Seelamantula, Chetan Singh Thakur

2020IEEE Signal Processing Letters30 citationsDOI

Abstract

We address the problem of 3-D reconstruction using neuromorphic cameras (also known as event-driven cameras), which are a new class of vision-inspired imaging devices. Neuromorphic cameras are becoming increasingly popular for solving image processing and computer vision problems as they have significantly lower data rates than conventional frame-based cameras. We develop a neuromorphic-camera-based Fringe Projection Profilometry (FPP) system. We use the Dynamic Vision Sensor (DVS) in the DAVIS346 neuromorphic camera for acquiring measurements. Neuromorphic FPP is faster than a single-line-scanning method. Also, unlike frame-based FPP, the efficacy of the proposed method is not limited by the background while acquiring measurements. The working principle of the DVS also allows one to efficiently handle shadows thereby preventing ambiguities during 2-D phase unwrapping.

Topics & Concepts

Neuromorphic engineeringArtificial intelligenceComputer visionComputer scienceFrame (networking)Projection (relational algebra)Frame rateProfilometerImage sensorComputer graphics (images)Artificial neural networkEngineeringAlgorithmTelecommunicationsSurface finishMechanical engineeringAdvanced Memory and Neural ComputingCCD and CMOS Imaging SensorsImage Processing Techniques and Applications
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