针对目前车载激光数据与全景影像配准问题存在的可靠性差、稳健性弱等问题，本项目以车载LiDAR移动测量系统中的激光扫描数据和全景影像数据为研究对象，重点研究全景影像和激光扫描点云几何特征的稳健提取方法，构建全景影像特征与车载激光扫描点云特征的可靠映射关系，建立稳健的全景影像与激光扫描点云高精度配准模型与求解方法，实现两类数据的高精度配准、融合以及优势互补。本项目的研究成果将为车载LiDAR移动测量系统提供一种简洁、高效、高精度的全景影像与车载激光扫描数据配准方法，为车载激光点云和全景影像的高精度融合、车载激光点云的几何目标提取以及具有高度真实感的街景三维模型重建等提供关键技术支撑，服务于数字地球、智慧城市、基础测绘、导航与位置服务等领域。

This proposal aims to solve the problems of the registration between mobile laser scanning point clouds and panoramic imagery. The main contributions of the proposal are as follows: (1) automated features extraction from mobile laser scanning point clouds; (2) automated features extraction from panoramic imagery; (3) robust corresponding relationship between the features from mobile laser scanning point clouds and panoramic imagery;and (4) reliable models for the accurate registration according to the robust corresponding relationship The outcomes of the proposal will be widely used for automated photo realistic 3D models generating, improve the efficiencies and effectiveness of 3D modeling using mobile laser point clouds, and produce beneficial services for digital earth,surveying and mapping, and location based services (LBS).