Abstract
This research will introduce an existing statistical curve fitting tool i.e. local regression into reverse engineering process. Instead of using the local regression on statistical data, it will be applied on 3D point clouds obtained from 3D scanners. As most 3D scanners capture the smallest surface details such as textured and non-smooth surfaces, it makes the 3D point cloud to surface conversion process problematic. By modifying this existing statistical tool of local regression with the proposed algorithm, it helps to smooth out rough surfaces obtained from 3D point cloud, minimising the error when generating the virtual surface from smoothened point cloud rather than from raw point cloud. The related method of performing the smoothening process on the 3D point will also be included in this paper. At the end, comparison of the smoothened point cloud and the unsmoothened point cloud will be visualised and discussed.
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