3 research outputs found

    Influence of Stereoscopic Camera System Alignment Error on the Accuracy of 3D Reconstruction

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    The article deals with the influence of inaccurate rotation of cameras in camera system alignment on 3D reconstruction accuracy. The accuracy of the all three spatial coordinates is analyzed for two alignments (setups) of 3D cameras. In the first setup, a 3D system with parallel optical axes of the cameras is analyzed. In this stereoscopic setup, the deterministic relations are derived by the trigonometry and basic stereoscopic formulas. The second alignment is a generalized setup with cameras in arbitrary positions. The analysis of the situation in the general setup is closely related with the influence of errors of the points' correspondences. Therefore the relation between errors of points' correspondences and reconstruction of the spatial position of the point was investigated. This issue is very complex. The worst case analysis was executed with the use of Monte Carlo method. The aim is to estimate a critical situation and the possible extent of these errors. Analysis of the generalized system and derived relations for normal system represent a significant improvement of the spatial coordinates accuracy analysis. A practical experiment was executed which confirmed the proposed relations

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

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    In this paper, we propose a new method for 3D object reconstruction using RGB-D sensor. The RGB-D sensor provides RGB images as well as depth images. Since the depth and RGB color images are captured with one sensor of a RGB-D camera placed in different locations, the depth image should be related to the color image. After matching of the images (registration), point-to-point corresponding between two images is found, and they can be combined and represented in the 3D space. In order to obtain a dense 3D map of the 3D object, we design an algorithm for merging information from all used cameras. First, features extracted from color and depth images are used to localize them in a 3D scene. Next, Iterative Closest Point (ICP) algorithm is used to align all frames. As a result, a new frame is added to the dense 3D model. However, the spatial distribution and resolution of depth data affect to the performance of 3D scene reconstruction system based on ICP. The presented computer simulation results show an improvement in accuracy of 3D object reconstruction using real data.This work was supported by the Russian Science Foundation, grant no. 17-76-20045

    Error analysis and experiments of 3D reconstruction using a RGB-D sensor

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