Projection of point cloud for basic object detection

Point cloud represents the set of measured points. Several methods for point cloud projection have already been proposed. These methods process measured points without angle rotation. We, however, believe that rotations of measurement points simplify whole object detection process. We propose to unfold a measured point cloud of indoor 3D space into single plane with preservation of height dimension. For unfolding of measured points we are using a suitable rotation matrix. This simplification allows to use a simpler methods for object detection. Described algorithm has been verified on several examples - indoor rooms.