Point cloud processing method and system based on random downsampling

The invention discloses a cloud processing method and system based on random reduced sampling points. The method comprises the following steps: carrying out local feature aggregation on an original point cloud; carrying out random downsampling on the point cloud after local feature aggregation; and processing the sparse point cloud after random downsampling. According to the method, simple and efficient random downsampling is adopted to greatly reduce the number of point clouds, and meanwhile, a specially designed feature aggregation strategy is adopted to ensure the retention of effective information, so that the spatial information and geometric information of the point clouds can be retained to the greatest extent under the condition of obviously reducing the calculation amount and memory occupation, and a more efficient and accurate processing result can be obtained. 本发明公开了一种基于随机降采样点云处理方法及系统，所述方法包括对原始点云进行局部特征聚合；对局部特征聚合后的点云进行随机降采样；对随机降采样后的稀疏点云进行处理。采用简单高效的随机降采样大大地减少点云数量，同时采用特别设计的特征聚合策略来保证有效信息的保留，能够在明显降低计算量和