The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012
Currently, data captured by Mobile Laser Scanners (MLS) is becoming a leading source for the mode... more Currently, data captured by Mobile Laser Scanners (MLS) is becoming a leading source for the modelling of building façade geometry. Automatic processing of MLS point clouds for feature extraction on building facades is a demanding work. Point cloud segmentation and recognition are the most important steps in this context. In this paper, a new approach for automatic and fast processing of MLS data for the detection of building patches while restricting to segment other features is introduced. After filtering of the point clouds, the building façade extraction takes place. An initial building point cluster detection and roughness based point separation within the cluster itself are the preliminary stages of this process. Thereafter points are segmented into planar patches based on the Random Sample Consensus (RANSAC) technique, as most facades are dominated by planar faces. An intelligent seed point selection method is introduced, and growing rules are applied in order to extract the most significant planar features which represent the building facades. Each segmented plane is afterwards processed to recognize the façade features. A rule based partitioning tree, constructed from the 2D geometric knowledge of building features is used for facade feature recognition. The approach has been tested with several urban data sets, and results demonstrate that the method can be applied in an efficient modelling process.
In this paper, we present a new approach for the generation and regularization of 3D roof boundar... more In this paper, we present a new approach for the generation and regularization of 3D roof boundaries in Airborne Laser scanner (ALS) data. Initially, segment based classification approach is chosen to discriminate off-terrain points from the terrain points and different rules are then imposed to extract as much of roof planes. We introduce the use of cycle graphs to the roof topology graph. The Dijkstra's algorithm is used to recognize the possible shortest closed cycles, and used such cycles for the fixing of ridge-line intersections. The subdivision of cycles is performed to handle step-edge intersections whilst union of connected cycles are taken for the manipulation of outer roof boundaries. Experimented results show that our approach is promising and can be obtained topologically valid, complete 3D roof structures.
ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012
In this paper, an automatic approach for the generation and regularization of 3D roof boundaries ... more In this paper, an automatic approach for the generation and regularization of 3D roof boundaries in Airborne Laser scanner data is presented. The workflow is commenced by segmentation of the point clouds. A classification step and a rule based roof extraction step are followed the planar segmentation. Refinement on roof extraction is performed in order to minimize the effect due to urban vegetation. Boundary points of the connected roof planes are extracted and fitted series of straight line segments. Each line is then regularized with respect to the dominant building orientation. We introduce the usage of cycle graphs for the best use of topological information. Ridge-lines and step-edges are basically extracted to recognise correct topological relationships among the roof faces. Inner roof corners are geometrically fitted based on the closed cycle graphs. Outer boundary is reconstructed using the same concept but with the outer most cycle graph. In here, union of the sub cycles is taken. Intermediate line segments (outer bounds) are intersected to reconstruct the roof eave lines. Two test areas with two different point densities are tested with the developed approach. Performance analysis of the test results is provided to demonstrate the applicability of the method.
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014
Geometrically and topologically correct 3D building models are required to satisfy with new deman... more Geometrically and topologically correct 3D building models are required to satisfy with new demands such as 3D cadastre, map updating, and decision making. More attention on building reconstruction has been paid using Airborne Laser Scanning (ALS) point cloud data. The planimetric accuracy of roof outlines, including step-edges is questionable in building models derived from only point clouds. This paper presents a new approach for the detection of accurate building boundaries by merging point clouds acquired by ALS and aerial photographs. It comprises two major parts: reconstruction of initial roof models from point clouds only, and refinement of their boundaries. A shortest closed circle (graph) analysis method is employed to generate building models in the first step. Having the advantages of high reliability, this method provides reconstruction without prior knowledge of primitive building types even when complex height jumps and various types of building roof are available. The...
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012
Currently, data captured by Mobile Laser Scanners (MLS) is becoming a leading source for the mode... more Currently, data captured by Mobile Laser Scanners (MLS) is becoming a leading source for the modelling of building façade geometry. Automatic processing of MLS point clouds for feature extraction on building facades is a demanding work. Point cloud segmentation and recognition are the most important steps in this context. In this paper, a new approach for automatic and fast processing of MLS data for the detection of building patches while restricting to segment other features is introduced. After filtering of the point clouds, the building façade extraction takes place. An initial building point cluster detection and roughness based point separation within the cluster itself are the preliminary stages of this process. Thereafter points are segmented into planar patches based on the Random Sample Consensus (RANSAC) technique, as most facades are dominated by planar faces. An intelligent seed point selection method is introduced, and growing rules are applied in order to extract the most significant planar features which represent the building facades. Each segmented plane is afterwards processed to recognize the façade features. A rule based partitioning tree, constructed from the 2D geometric knowledge of building features is used for facade feature recognition. The approach has been tested with several urban data sets, and results demonstrate that the method can be applied in an efficient modelling process.
In this paper, we present a new approach for the generation and regularization of 3D roof boundar... more In this paper, we present a new approach for the generation and regularization of 3D roof boundaries in Airborne Laser scanner (ALS) data. Initially, segment based classification approach is chosen to discriminate off-terrain points from the terrain points and different rules are then imposed to extract as much of roof planes. We introduce the use of cycle graphs to the roof topology graph. The Dijkstra's algorithm is used to recognize the possible shortest closed cycles, and used such cycles for the fixing of ridge-line intersections. The subdivision of cycles is performed to handle step-edge intersections whilst union of connected cycles are taken for the manipulation of outer roof boundaries. Experimented results show that our approach is promising and can be obtained topologically valid, complete 3D roof structures.
ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012
In this paper, an automatic approach for the generation and regularization of 3D roof boundaries ... more In this paper, an automatic approach for the generation and regularization of 3D roof boundaries in Airborne Laser scanner data is presented. The workflow is commenced by segmentation of the point clouds. A classification step and a rule based roof extraction step are followed the planar segmentation. Refinement on roof extraction is performed in order to minimize the effect due to urban vegetation. Boundary points of the connected roof planes are extracted and fitted series of straight line segments. Each line is then regularized with respect to the dominant building orientation. We introduce the usage of cycle graphs for the best use of topological information. Ridge-lines and step-edges are basically extracted to recognise correct topological relationships among the roof faces. Inner roof corners are geometrically fitted based on the closed cycle graphs. Outer boundary is reconstructed using the same concept but with the outer most cycle graph. In here, union of the sub cycles is taken. Intermediate line segments (outer bounds) are intersected to reconstruct the roof eave lines. Two test areas with two different point densities are tested with the developed approach. Performance analysis of the test results is provided to demonstrate the applicability of the method.
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014
Geometrically and topologically correct 3D building models are required to satisfy with new deman... more Geometrically and topologically correct 3D building models are required to satisfy with new demands such as 3D cadastre, map updating, and decision making. More attention on building reconstruction has been paid using Airborne Laser Scanning (ALS) point cloud data. The planimetric accuracy of roof outlines, including step-edges is questionable in building models derived from only point clouds. This paper presents a new approach for the detection of accurate building boundaries by merging point clouds acquired by ALS and aerial photographs. It comprises two major parts: reconstruction of initial roof models from point clouds only, and refinement of their boundaries. A shortest closed circle (graph) analysis method is employed to generate building models in the first step. Having the advantages of high reliability, this method provides reconstruction without prior knowledge of primitive building types even when complex height jumps and various types of building roof are available. The...
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Papers by Sanka Perera