Efficiency of grid representation and its algorithms for areal 3D scan data

Abstract

This paper describes the efficiency of a grid representation for an areal 3D scan data and the algorithms for managing measurement data captured by areal 3D scanners. Due to the measurement principles of areal 3D scanners, a measurement point is generated for each pixel of the imaging sensor inside the 3D scanner. Therefore, when the measurement points are perspectively projected on the image plane of the imaging sensor, each point has one-to-one correspondence to the imaging elements of the sensor that has a regular grid structure. By using this property, measurement points are represented by their depth values in a grid representation model. Compared to the conventional representation model, such as triangular mesh and cloud of points, the grid representation uses less memory and allows efficient algorithms for processing the measurement data captured by areal 3D scanners.