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Linear Correction and Matching Method for 3D Line Structure Reconstruction

机译:3D线结构重建线性校正和匹配方法

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The 3D reconstruction technique using the straight-line segments as features has high precision and low computational cost. The method is especially suitable for large-scale urban datasets. However, the line matching step in the existing method has a mismatching problem. The two main reasons for this problem are the line detection result is not located at the true edge of the image and there is no consistency check of the matching pair. In order to solve this problem, a linear correction and matching method for 3D reconstruction of target line structure is proposed in this paper. Firstly, the edge features of the image are extracted to obtain a binarized edge map. Then, the extended gradient map is calculated using the edge map and the gradient to establish the gradient gravitational map. Secondly, the straight-line detection method is used to extract all the linear features used for the 3D reconstruction image, and the linear position is corrected by the gradient gravitational map. Finally, the point feature matching result is used to calculate the polar line, and the line matching results of the adjacent three images are used to determine the final partial check feature area. Then, random sampling is used to obtain the feature similarity check line matching result in the small neighborhood. The aforementioned steps can eliminate the mismatched lines. The experimental results demonstrate that the 3D model obtained using the proposed method has higher integrity and accuracy than the existing methods.
机译:使用直线段的3D重建技术作为特征具有高精度和低计算成本。该方法特别适用于大型城市数据集。但是,现有方法中的线路匹配步骤具有不匹配的问题。此问题的两种主要原因是线路检测结果未位于图像的真实边缘,并且没有匹配对的一致性检查。为了解决该问题,本文提出了一种针对目标线结构的三维重建线性校正和匹配方法。首先,提取图像的边缘特征以获得二值化边缘图。然后,使用边缘图和梯度来计算扩展梯度图以建立梯度重力地图。其次,使用直线检测方法来提取用于3D重建图像的所有线性特征,并且通过梯度重力映射校正线性位置。最后,使用点特征匹配结果来计算极坐标线,并且使用相邻三个图像的线匹配结果来确定最终部分检查特征区域。然后,随机采样用于获得小邻域中的特征相似性检查线匹配结果。上述步骤可以消除不匹配的线路。实验结果表明,使用所提出的方法获得的3D模型具有比现有方法更高的完整性和准确性。

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