Intelligent Measurement Processes in 3D Optical Metrology: Producing More Accurate Point Clouds

Abstract

Point clouds are usually treated as raw data to be cleaned up afterwards, with the accuracy fixed at the moment of capture. Charles Mony, Daniel Brown and Patrick Hebert argue for making the measurement process itself intelligent – letting what has already been measured inform how the next measurement is taken – so that the cloud that comes out is more accurate rather than merely larger.