Due to the difficulty in obtaining multi-modal point cloud data in complex environments, the requirements for point cloud data registration and 3D model construction accuracy are becoming increasingly high, this article takes the real-life 3D modeling of Nantong Grand Theater as an example. When the position difference between the initial point cloud and the calibration point cloud is significant, using the ICP algorithm for point cloud registration can easily lead to local optimization problems. The proposed nearest point iteration (CPA-ICP) algorithm based on control point auxiliary constraints is used to register point cloud data, and the experimental comparison of the other three point cloud registration algorithms fully demonstrates, This method has high registration accuracy and efficiency, and has good reference significance for multimodal point cloud data fusion in complex scenes.
关键词
复杂场景/多模态点云/联合定向匹配/CPA-ICP算法/数据融合
Key words
complex scenarios/multi-modal point cloud/joint directional matching/CPA-ICP algorithm/data fusion
维普
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