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Robust RGB-D Data Registration Based on Correntropy and Bi-directional Distance

机译:基于管置和双向距离的强大RGB-D数据登记

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The iterative closest point (1CP) algorithm is most widely used for rigid registration of point sets. In this paper, a robust ICP registration method data is proposed to register RGB-D data. Firstly, the color information is introduced to build more precise correspondence between two point sets. Secondly, to enhance the robustness of the algorithm to noise and outliers, the maximum correntropy criterion (MCC) is introduced to the registration framework. Thirdly, to reduce the possibility of the algorithm falling into local minimum and deal with ill-pose issue, the bidirectional distance measurement is added to the proposed algorithm. Finally, the experimental results of point sets registration and scene reconstruction demonstrate that the proposed algorithm can obtain more precise and robust results than other ICP algorithms.
机译:迭代最接近点(1CP)算法最广泛地用于点集的刚性配准。本文提出了一种稳健的ICP注册方法数据来注册RGB-D数据。首先,引入颜色信息以在两个点集之间构建更精确的对应关系。其次,为了增强算法对噪声和异常值的稳健性,将最大的正轮内标准(MCC)引入登记框架。第三,为了减少算法落入局部最小的可能性并处理不良问题,将双向距离测量添加到所提出的算法中。最后,点设置登记和场景重建的实验结果表明,所提出的算法可以获得比其他ICP算法更精确和稳健的结果。

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