Three-dimensional feature description for a local surface is a core technology in 3D computer vision. Existing descriptors perform poorly in terms of distinctiveness and robustness owing to noise, mesh decimation, clutter, and occlusion in real scenes. In this paper, we propose a 3D local surface descriptor using point-pair transformation feature histograms (PPTFHs) to address these challenges. The generation process of the PPTFH descriptor consists of three steps. First, a simple but efficient strategy is introduced to partition the point-pair sets on the local surface into four subsets. Then, three feature histograms corresponding to each point-pair subset are generated by the point-pair transformation features, which are computed using the proposed Darboux frame. Finally, all the feature histograms of the four subsets are concatenated into a vector to generate the overall PPTFH descriptor. The performance of the PPTFH descriptor is evaluated on several popular benchmark datasets, and the results demonstrate that the PPTFH descriptor achieves superior performance in terms of descriptiveness and robustness compared with state-of-the-art algorithms. The benefits of the PPTFH descriptor for 3D surface matching are demonstrated by the results obtained from five benchmark datasets.

中文翻译：

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基于点对变换特征的鲁棒局部描述符用于3D表面匹配

局部表面的三维特征描述是3D计算机视觉中的一项核心技术。现有的描述符由于在真实场景中的噪声，网格抽取，杂波和遮挡而在独特性和鲁棒性方面表现不佳。在本文中，我们提出了一种使用点对变换特征直方图（PPTFH）的3D局部表面描述符，以解决这些挑战。PPTFH描述符的生成过程包括三个步骤。首先，引入一种简单而有效的策略，将局部表面上的点对集划分为四个子集。然后，通过点对变换特征生成与每个点对子集相对应的三个特征直方图，这些特征直方图是使用提出的Darboux帧计算的。最后，将四个子集的所有特征直方图连接到一个向量中，以生成整体PPTFH描述符。在多个流行的基准数据集上评估了PPTFH描述符的性能，结果表明，与最新算法相比，PPTFH描述符在描述性和鲁棒性方面均具有出色的性能。从5个基准数据集中获得的结果证明了PPTFH描述符对3D表面匹配的好处。