现有接触网的三维重建所需时间较长,工作繁琐,为解决此类问题,本文提出采用自动重建法利用点云数据实现其零部件的三维重建.点云配准是影响重建过程准确度及效率的重要因素,而目前普遍使用的SIFT匹配算法,由于构建的关键点特征向量维数高,计算量大,导致匹配速度慢.为解决此问题,本文提出利用均匀模式LBP特征值描述SIFT关键点,获取关键点特征向量,并用向量间的距离判断关键点的相似性,以确定关键点的对应关系,完成配准和重建,得到接触网零部件的三维模型.结果表明,本文所提算法可行有效,能提高匹配速度,加速三维重建.%The methods of 3D reconstruction of catenary system currently used are time-consuming and full of heavy workload . In order to address this problem , a method using optical instruments to acquire point cloud data for the automated reconstruction of catenary parts was proposed in this paper . The process of point cloud registration is crucial to the efficiency and accuracy of the entire 3D reconstruction process . The SIFT algo-rithm is known as the most widely used local feature-based matching algorithm with high performance ,but the intensive computation and high vector dimension of building eigenvectors for key points affect matching speed . To solve this problem , LBP eigenvalues in uniform pattern were used to describe the SIFT key points to obtain the eigenvectors of the key points . The distance between vectors was used to determine the similarity of key points to identify the correspondence of two key points in different point clouds . Then coarse registration ,fine registration and surface reconstruction were completed ,and the 3D reconstruction model of catenary parts was finally finished . Experimental results show that the proposed algorithm is able to realize the objective of impro-ving the matching speed , thus speeding up reconstruction process .
展开▼
