A Fast Sliding Voxel approach to detect 3D Planes in Unorganized Point Clouds

抄録

3D planes are figures with low geometric features, however, they have important applications in computer vision, such as object recognition, autonomous navigation and key points detection. Current methods are precise, but non-deterministic and slow; therefore, in the past we proposed a deterministic Hough Transform based method and confirmed faster speed and improved accuracy. Nonetheless, the number of parameters were big; thus, motivated on the sliding window methods in 2D, in this work we created a 3D Sliding Voxel approach to detect planar surfaces with less parameters, faster speed and higher accuracy.