Abstract

Three-dimensional (3D) modeling of objects play an important role in quality assurance, re-engineering of an object, and mapping of interior design for quality measurements. Hence, this field proves to be one of the hot research topics in the field of robotics. Although, using laser scanner is the most common method for 3D point cloud, the camera-based methods are also introduced in this field. In this paper, we propose and analyze two methods for making 3D point cloud for any given object. First one is camera-based 3D point cloud using structure from motion technique and secondly the laser scanner-based 3D point cloud. The result shows that camera-based 3D point cloud method produced dense point cloud but prone to outliers, whereas the laser scanner method is robust. It should also be noted that the camera is multiple times cost effective than laser scanner.

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