Abstract:
A method and apparatus for rendering geographic areas involves presenting at least part of the geographic area in a distinctive fashion. An area of interest is identified. A location of the area of interest as a geographic sub-area within a geographic area is determined. A representation of the area of interest within an electronic model of the geographic area is located. A view of the electronic model of the geographic area comprising the representation of the area of interest is selected, and the view of the electronic model with the area of interest having a different display characteristic than other geographic sub-areas shown in the view is presented. The different display characteristic distinguishes the area of interest from the other geographic sub-areas.
Abstract:
Systems, apparatuses, and methods are provided for refining building alignment in an aerial image. At least one candidate shifting vector and matching score value are determined for a local building. At least one dominant shifting vector is determined for at least one random group of neighboring buildings of the local building. At least one optimized matching score is calculated using the at least one candidate shifting vector for the local building and the at least one dominant shifting vector for the at least one random group of the neighboring buildings. A final shifting vector for the local building is found using the at least one optimized matching score.
Abstract:
A computing device performs matching between a target image and one or more template images. The computing device receives image data and performs an edge detection algorithm on the image data. The edge detection algorithm includes a distance metric based on angles between gradient vectors in the image data and gradient vectors in one or more templates. The computing device matches a building model to the image data based on results of the edge detection algorithm, wherein the building model is associated with the one or more templates.
Abstract:
Systems, apparatuses, and methods are provided for three-dimensional modeling of building roofs using three-dimensional point cloud data. Point cloud data of a roof of a building is received, and roof data points are selected or extracted from the point cloud data. Semantic type classifications are calculated for each selected roof data point. Roof styles are determined from the semantic type classifications, and a synthetic model of the roof and building is rendered based on the determined roof style.
Abstract:
Systems, apparatuses, and methods are provided for refining building alignment in an aerial image. At least one candidate shifting vector and matching score value are determined for a local building. At least one dominant shifting vector is determined for at least one random group of neighboring buildings of the local building. At least one optimized matching score is calculated using the at least one candidate shifting vector for the local building and the at least one dominant shifting vector for the at least one random group of the neighboring buildings. A final shifting vector for the local building is found using the at least one optimized matching score.
Abstract:
Structure boundaries may be determined by receiving a plurality of three dimensional (3D) data points representing a geographic area. The 3D data points may be projected into a two dimensional (2D) grid comprised of area elements. A structure boundary may be determined based on an analysis of the area elements.
Abstract:
A method and apparatus for rendering geographic areas involves presenting at least part of the geographic area in a distinctive fashion. An area of interest is identified. A location of the area of interest as a geographic sub-area within a geographic area is determined. A representation of the area of interest within an electronic model of the geographic area is located. A view of the electronic model of the geographic area comprising the representation of the area of interest is selected, and the view of the electronic model with the area of interest having a different display characteristic than other geographic sub-areas shown in the view is presented. The different display characteristic distinguishes the area of interest from the other geographic sub-areas.
Abstract:
Structure boundaries may be determined by receiving a plurality of three dimensional (3D) data points representing a geographic area. The 3D data points may be projected into a two dimensional (2D) grid comprised of area elements. A structure boundary may be determined based on an analysis of the area elements.
Abstract:
A method, apparatus and computer program product are provided for roof type classification and reconstruction based on two dimensional aerial images. In the context of a method, the method includes receiving a roof image, determining a segmentation of the roof image based on cutting lines associated with roof features and classifying roof segments based on roof features within the segment. The classifying roof segments is based on the roof features correlation to a roof type pattern.
Abstract:
A computing device performs matching between a target image and one or more template images. The computing device receives image data and performs an edge detection algorithm on the image data. The edge detection algorithm includes a distance metric based on angles between gradient vectors in the image data and gradient vectors in one or more templates. The computing device matches a building model to the image data based on results of the edge detection algorithm, wherein the building model is associated with the one or more templates.