基于RGB-D数据的颜色引导粗配准方法

Benyue Su, Wei Han, Yusheng Peng, Min Sheng
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引用次数: 0

摘要

提出了一种基于RGB-D数据的粗配准方法。从混合特征中获得特征点。根据特征描述符在目标点云中搜索特征点对应的点。将特征点划分为若干分区,计算每个分区中对应点对之间的刚性变换。从每个分区的刚性变换中选择最优的刚性变换。混合特征由相邻点的几何信息和颜色信息构成。特征描述符由混合特征和归一化RGB值构建。实验结果表明,该方法对RGB-D数据是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Color-Guided Coarse Registration Method Based on RGB-D Data
This paper proposes a coarse registration method based on RGB-D data. The feature points are obtained from the mixed feature. The corresponding points of the feature points are searched in target point cloud according to the feature descriptor. The feature points are divided into several partitions and the rigid transformation is calculated between the corresponding point pairs in each partition. The optimal rigid transformation is chosen from the rigid transformation of each partition. The mixed feature is constructed by geometric information and color information of the neighborhood points. The feature descriptor is built with the mixed feature and normalized RGB value. The experimental results demonstrated that the method is effective for RGB-D data.
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