集装箱锁销曲面结构复杂, 因而建立出一个曲面特征完整度较高的点云模型较为困难. 考虑到在大多数场景下, 位于固定高度的传感器搭配旋转的转台采集的曲面特征通常会存在一定的缺失. 为此, 提出了一种基于转台的多视角多姿态点云模型重建算法, 还原锁销较完整的曲面特征. 首先, 利用转台参数标定结果, 实现多视角三维点云的拼接, 建立一个固定姿态下的点云模型; 其次, 通过提出的改进球面投影算法, 选取锁销置于转台的摆放姿态, 建立另一姿态下的点云模型; 最后, 融合多个姿态下的点云模型, 提高其具备的曲面特征. 实验结果表明, 所提出的算法能建立出曲面特征完整度较高的锁销点云模型.

The surface structure of a container lock pin is complex, making it difficult to establish a point cloud model with a high surface feature integrity. Therefore, a multi-view and multi-attitude point cloud model reconstruction algorithm based on a turntable was proposed to restore the complete surface features of the locking pin. Considering that sensors at a fixed height are paired with rotating turntables in most scenarios, the collected surface features are usually somewhat missing. Initially, the algorithm uses the parameter calibration results of the turntable to realize the multi-view three-dimensional point cloud stitching, and establishes a fixed attitude point cloud model. Then, through the proposed improved spherical projection algorithm, the positioning of the locking pin on the turntable is selected to establish a point cloud model under another posture. Finally, the point cloud model with multiple attitudes is integrated to improve its surface characteristics. Experimental results show that the proposed algorithm can build a lock-pin point cloud model with high surface feature integrity.