Improved low-cost 3D reconstruction pipeline by merging data from different color and depth cameras

The performance of traditional 3D capture methods directly influences the quality of digitally reconstructed 3D models. In order to obtain complete and well-detailed low-cost three-dimensional models, this paper proposes a 3D reconstruction pipeline using point clouds from different sensors, combining captures of a low-cost depth sensor post-processed by Super-Resolution techniques with high-resolution RGB images from an external camera using Structure from Motion and Multi-View Stereo output data. The main contribution of this work includes the description of a complete pipeline that improves the stage of information acquisition and merges data from different sensors. Several phases of the 3D reconstruction pipeline were also specialized to improve the model's visual quality. The experimental evaluation demonstrates that the developed method produces good and reliable results for low-cost 3D reconstruction of an object.