We present an accurate and automatic bottom-up floorplan reconstruction method by leveraging geometric priors extracted from raw point clouds of indoor scenes. Compared to two state-of-theart methods which adopt point density as priors only, our designed geometric priors integrate point density with indoor area recognition and normal information. These geometric priors are used to calculate the confidence score for each unit region as part of the external boundaries. A cost function is developed according to the confidence scores and the normals along a certain edge, as well as the edge length...
