Accuracy analysis of 3D object reconstruction using RGB-D sensor

Abstract

The geometry of an object can be reconstructed from laser range scans, a set of different photos, monocular cameras and stereo cameras; each technology possesses disadvantages and limitations. RGB-D cameras like Microsoft Kinect or ASUS Xtion Pro are sensing systems equipped with an RGB camera, infrared projector, and infrared sensor. They can gather RGB information and the depth map simultaneously. The ICP (Iterative Closest Point) is one of the most commonly used methods for pairwise alignment, where the rotation and translation to align two point clouds are determined. Many variants on the base ICP algorithm were proposed because of the limitations in the ICP algorithm: different cost functions [11] and others [12]; two-Pass ICP with color constraint to improve the error minimization process [13]; 3D representation using a set of planes to perform the registration [14]; point-to-plane matchings instead of point-to-point matchings in standard

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