Research into object deformations using computer vision techniques has been under intense study in recent years. A widely used technique is 3D non-rigid registration to estimate the transformation between two instances of a deforming structure. Despite many previous developments on this topic, it remains a challenging problem. In this paper we propose a novel approach to non-rigid registration combining two data spaces in order to robustly calculate the correspondences and transformation between two data sets. In particular, we use point color as well as 3D location as these are the common outputs of RGB-D cameras. We have propose the Color Coherent Point Drift (CCPD) algorithm (an extension of the CPD method [1]). Evaluation is performed using synthetic and real data. The synthetic data includes easy shapes that allow evaluation of the effect of noise, outliers and missing data. Moreover, an evaluation of realistic figures obtained using Blensor is carried out. Real data acquired using a general purpose Primesense Carmine sensor is used to validate the CCPD for real shapes. For all tests, the proposed method is compared to the original CPD showing better results in registration accuracy in most cases.
翻译:近些年来,对使用计算机视觉技术的物体变形进行了大量研究。一种广泛使用的技术是3D非硬化登记,以估计变形结构两种情况之间的变异。尽管以前有许多关于这个专题的发展,但它仍然是一个具有挑战性的问题。在本文件中,我们提议对非硬化登记采取新的办法,将两个数据空间结合起来,以稳健地计算两个数据集之间的对应和变异。特别是,我们使用点色和3D位置作为 RGB-D 相机的共同产出。我们提出了色 Coherent Point Drift (CPD) 算法(CPD 方法的延伸[1] );评价是使用合成和真实数据进行的。合成数据包括便于评价噪音、外源和缺失数据的影响的简单形状。此外,对使用Blensor 获得的现实数字进行了评估。使用通用Presense Carmin传感器获得的真实数据用于验证真形CCPD。所有测试都将拟议方法与原始CPD(CPD)进行比较,显示在大多数情况下登记准确性结果较好。