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Three-Dimensional Measurement Method of Four-View Stereo Vision Based on Gaussian Process Regression
Multisensor systems can overcome the limitation of measurement range of single-sensor systems, but often require complex calibration and data fusion. In this study, a three-dimensional (3D) measurement method of four-view stereo vision based on Gaussian process (GP) regression is proposed. Two sets of point cloud data of the measured object are obtained by gray-code phase-shifting technique. On the basis of the characteristics of the measured object, specific composite kernel functions aredoi:10.3390/s19204486 fatcat:l7xbkzdkabagvgmh7gdlykzi7a