Abstract: Automated methods and systems are disclosed that classify a first component and a second component of a roof with data points being part of, or extracted from, at least one image and/or point cloud. The first component and the second component may have a polygonal base and at least one edge. Evidence of a soft constraint and a hard constraint may be identified via the data points and such evidence may be associated with the first component and the second component. At least one hypothesis model of the roof may be generated using relationships between the first component and the second component, the soft constraint and the hard constraint. The hypothesis model may be transformed into a three-dimensional model. The three-dimensional model may be used to generate a roof report of the roof.

Abstract: Automated methods and systems are disclosed that classify a first component and a second component of a roof with data points being part of, or extracted from, at least one image and/or point cloud. The first component and the second component may have a polygonal base and at least one edge. Evidence of a soft constraint and a hard constraint may be identified via the data points and such evidence may be associated with the first component and the second component. At least one hypothesis model of the roof may be generated using relationships between the first component and the second component, the soft constraint and the hard constraint. The hypothesis model may be transformed into a three-dimensional model. The three-dimensional model may be used to generate a roof report of the roof.

Abstract: An automated method is disclosed that classifies a first component and a second component of a roof with data points being part of, or extracted from at least one image. The first component and the second component have a ridge, at least one eave parallel to the ridge and a rectangular base. Evidence of a soft constraint and a hard constraint is identified via the data points and such evidence is associated with the first component and the second component. At least one hypothesis model of the roof is generated using relationships between the first component and the second component, the soft constraint and the hard constraint. The hypothesis model is transformed into a three dimensional model, and the three dimensional model is used to generate a roof report of the roof.

Abstract: An automated method is disclosed that classifies a first component and a second component of a roof with data points being part of, or extracted from at least one image. The first component and the second component have a ridge, at least one eave parallel to the ridge and a rectangular base. Evidence of a soft constraint and a hard constraint is identified via the data points and such evidence is associated with the first component and the second component. At least one hypothesis model of the roof is generated using relationships between the first component and the second component, the soft constraint and the hard constraint. The hypothesis model is transformed into a three dimensional model, and the three dimensional model is used to generate a roof report of the roof.