Institute of Electronics and Informatics Engineering of Aveiro, University of Aveiro, 3810-193 Aveiro, Portugal.
Department of Mechanical Engineering, University of Aveiro, 3810-193 Aveiro, Portugal.
Sensors (Basel). 2020 Mar 9;20(5):1497. doi: 10.3390/s20051497.
Three-dimensional (3D) reconstruction methods generate a 3D textured model from the combination of data from several captures. As such, the geometrical transformations between these captures are required. The process of computing or refining these transformations is referred to as alignment. It is often a difficult problem to handle, in particular due to a lack of accuracy in the matching of features. We propose an optimization framework that takes advantage of fiducial markers placed in the scene. Since these markers are robustly detected, the problem of incorrect matching of features is overcome. The proposed procedure is capable of enhancing the 3D models created using consumer level RGB-D hand-held cameras, reducing visual artefacts caused by misalignments. One problem inherent to this solution is that the scene is polluted by the markers. Therefore, a tool was developed to allow their removal from the texture of the scene. Results show that our optimization framework is able to significantly reduce alignment errors between captures, which results in visually appealing reconstructions. Furthermore, the markers used to enhance the alignment are seamlessly removed from the final model texture.
三维（3D）重建方法通过组合来自多次拍摄的数据生成 3D 纹理模型。因此，需要这些拍摄之间的几何变换。计算或细化这些变换的过程称为对齐。由于特征匹配的精度不足，因此这通常是一个难以处理的问题。我们提出了一种利用放置在场景中的基准标记的优化框架。由于这些标记可以被稳健地检测到，因此克服了特征匹配不正确的问题。所提出的过程能够增强使用消费级 RGB-D 手持相机创建的 3D 模型，减少因未对准而导致的视觉伪影。该解决方案固有的一个问题是场景被标记污染。因此，开发了一种工具来允许从场景的纹理中去除这些标记。结果表明，我们的优化框架能够显著减少拍摄之间的对齐误差，从而产生视觉上吸引人的重建。此外，用于增强对齐的标记从最终模型纹理中无缝去除。
