In this paper,for the problem that the current algorithm is not ideal for complex scene segmentation,a region clustering algorithm based on supervoxel is proposed. Firstly,by using the latest algorithm,the hypervoxel is obtained by over-segmented the point cloud. Secondly,by calculating the elevation difference between the seed supervoxel and its first adjacent block,the area to be merged is determined as planes or parallel to the ground and other surfaces,The similarity measure between the current clustering region and the adjacent blocks is merged by using different normal vector included angle threshold and automatically obtained orthogonal distance threshold. In order to prevent under segmentation in the clustering process,each time when a new supervoxel is added,the geometric information such as the normal vector of the current cluster block is updated. Finally,both quantitative and qualitative comparisons are performed through two types of algorithms. The experimental results show that this algorithm is accurate and reliable for complex scene segmentation.
LI Wen, LIU De-er, WANG You-yi, LIU Peng, SHI Gui-gang. Complex scene segmentation based on supervoxel region clustering[J]. LASER & INFRARED,2021,51(11):1425~1432