论文标题

有效的纹理映射通过非题量的全局纹理对齐

Efficient texture mapping via a non-iterative global texture alignment

论文作者

Rouhani, Mohammad, Fradet, Matthieu, Baillard, Caroline

论文摘要

纹理重建技术通常会遭受关键帧姿势中的错误。我们提出了一种非著作方法,用于给定3D场景的无缝纹理重建。我们的方法使用全局优化框架在单次拍摄中找到了最佳的纹理对齐。首先,我们会自动选择最佳的密钥帧来纹理网格的每个脸部。这导致将网格分解为与同一密钥帧相关的一小组连接面。我们称之为这样的组碎片。然后,我们提出了在片段边界周围提取的3D关键点之间的几何感知匹配技术,其中匹配区由边缘大小控制。这些约束导致最小二乘(LS)模型来找到最佳的对齐。最后,通过应用快速校正进一步降低视觉接缝。与像素方面的方法相反,我们通过求解稀疏的线性方程系统来找到最佳的对齐,该线性方程非常快速且非词语。实验结果表明,与其他比对方法相比,计算复杂性和表现低得多。

Texture reconstruction techniques generally suffer from the errors in keyframe poses. We present a non-iterative method for seamless texture reconstruction of a given 3D scene. Our method finds the best texture alignment in a single shot using a global optimisation framework. First, we automatically select the best keyframe to texture each face of the mesh. This leads to a decomposition of the mesh into small groups of connected faces associated to a same keyframe. We call such groups fragments. Then, we propose a geometry-aware matching technique between the 3D keypoints extracted around the fragment borders, where the matching zone is controlled by the margin size. These constraints lead to a least squares (LS) model for finding the optimal alignment. Finally, visual seams are further reduced by applying a fast colour correction. In contrast to pixel-wise methods, we find the optimal alignment by solving a sparse system of linear equations, which is very fast and non-iterative. Experimental results demonstrate low computational complexity and outperformance compared to other alignment methods.

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