In this article, we proposed a fast algorithm of symmetry detection 3D model. First, we used the PCA algorithm for initial symmetry detection. Then, using exhaustive search of symmetry planes passing through the center of gravity about the initial symmetry plane, we determined the optimal symmetry plane with the help of the modified Hausdorff metric. The accuracy and speed of the proposed symmetry detection algorithm on real and synthetic data are compared to the PCA algorithm.
KEYWORDS: Reconstruction algorithms, 3D modeling, Sensors, RGB color model, Clouds, Cameras, 3D image processing, Image registration, 3D image reconstruction
In this paper, we propose a new algorithm for dense 3D object reconstruction using a RGB-D sensor at high rate. In order to obtain a dense shape recovery of a 3D object, an efficient merging of the current and incoming point clouds obtained with the Iterative Closest Point is suggested. As a result, incoming frames are aligned to the dense 3D model. The accuracy of the proposed 3D object reconstruction algorithm on real data is compared to that of the estate-of-the-art reconstruction algorithms.
KEYWORDS: Denoising, Reconstruction algorithms, Digital filtering, Magnetorheological finishing, 3D modeling, Image filtering, Data modeling, Nonlinear filtering, RGB color model, Clouds
In this paper, we estimate the accuracy of 3D object reconstruction using depth filtering and data from a RGB-D sensor. Depth filtering algorithms carry out inpainting and upsampling for defective depth maps from a RGB-D sensor. In order to improve the accuracy of 3D object reconstruction, an efficient and fast method of depth filtering is designed. Various methods of depth filtering are tested and compared with respect to the reconstruction accuracy using real data. The presented results show an improvement in the accuracy of 3D object reconstruction using depth filtering from a RGB-D sensor.
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