Abstract: A method and related software are disclosed for processing imagery related to three dimensional models. To display new visual data for select portions of images, an image of a physical structure such as a building with a façade is retrieved with an associated three dimensional model for that physical structure according to common geolocation tags. A scaffolding of surfaces composing the three dimensional model is generated and regions of the retrieved image are registered to the surfaces of the scaffolding to create mapped surfaces for the image. New image data such as texture information is received and applied to select mapped surfaces to give the retrieved image the appearance of having the new texture data at the selected mapped surface.

Abstract: A method and related software are disclosed for processing imagery related to three dimensional models. To display new visual data for select portions of images, an image of a physical structure such as a building with a façade is retrieved with an associated three dimensional model for that physical structure according to common geolocation tags. A scaffolding of surfaces composing the three dimensional model is generated and regions of the retrieved image are registered to the surfaces of the scaffolding to create mapped surfaces for the image. New image data such as texture information is received and applied to select mapped surfaces to give the retrieved image the appearance of having the new texture data at the selected mapped surface.

Abstract: A system is provided including a database that ingests data from disparate image sources, with a variety of image metadata types and qualities, and manages images geospatially through the creation and continued refinement of camera solutions for each data object included. These camera solutions are calculated and refined by the database as additional data enters the system that could affect the solutions, through a combination of the application of image metadata towards image processing methods and the use of optical-only computer vision techniques. The database continually generates data quality metrics and relevant imagery and geometry analytics, which drive future collection tasking, system analytics, and human quality control requirements.

Abstract: A system is provided including a database that ingests data from disparate image sources, with a variety of image metadata types and qualities, and manages images geospatially through the creation and continued refinement of camera solutions for each data object included. These camera solutions are calculated and refined by the database as additional data enters the system that could affect the solutions, through a combination of the application of image metadata towards image processing methods and the use of optical-only computer vision techniques. The database continually generates data quality metrics and relevant imagery and geometry analytics, which drive future collection tasking, system analytics, and human quality control requirements.

Abstract: A system and method is provided for scaling and constructing a multi-dimensional (e.g., 3D) building model using ground-level imagery. Ground-level imagery is used to identify architectural elements that have known architectural standard dimensional ratios. Dimensional ratios of architectural elements in the multi-dimensional building model (unscaled) are compared with known architectural standard dimensional ratios to scale and construct an accurate multi-dimensional building model.

Abstract: A system is provided including a database that ingests data from disparate image sources, with a variety of image metadata types and qualities, and manages images geospatially through the creation and continued refinement of camera solutions for each data object included. These camera solutions are calculated and refined by the database as additional data enters the system that could affect the solutions, through a combination of the application of image metadata towards image processing methods and the use of optical-only computer vision techniques. The database continually generates data quality metrics and relevant imagery and geometry analytics, which drive future collection tasking, system analytics, and human quality control requirements.

Abstract: A system and method is provided for identifying error and rescaling and constructing or reconstructing a multi-dimensional (e.g., 3D building) model using known architectural dimensions. The system identifies architectural elements that have known architectural standard dimensions. Dimensional measurements of architectural elements in the multi-dimensional model (poorly scaled) are compared with known architectural standard dimensions to rescale and construct/reconstruct an accurate multi-dimensional building model.

Abstract: Imagery is used to identify architectural elements that have known architectural patterns. Feature sets associated with a surface and architectural elements in a building model image are compared with known architectural standards of materials to determine the surface building materials and architectural details of a textured building model. In addition, specific texture patterns can assist final material selections for a repair/replacement.

Abstract: A system and method is provided for identifying error and rescaling and constructing or reconstructing a multi-dimensional (e.g., 3D building) model using known architectural dimensions. The system identifies architectural elements that have known architectural standard dimensions. Dimensional measurements of architectural elements in the multi-dimensional model (poorly scaled) are compared with known architectural standard dimensions to rescale and construct/reconstruct an accurate multi-dimensional building model.

Abstract: A system and method is provided for identifying error and rescaling and constructing or reconstructing a multi-dimensional (e.g., 3D) building model using street-level imagery. Street-level imagery is used to identify architectural elements that have known architectural standard dimensions. Dimensional measurements of architectural elements in the multi-dimensional building model (poorly scaled) are compared with known architectural standard dimensions to rescale and construct/reconstruct an accurate multi-dimensional building model.

Abstract: A system and method is provided for scaling and constructing a multi-dimensional (e.g., 3D) building model using ground-level imagery. Ground-level imagery is used to identify architectural elements that have known architectural standard dimensional ratios. Dimensional ratios of architectural elements in the multi-dimensional building model (unscaled) are compared with known architectural standard dimensional ratios to scale and construct an accurate multi-dimensional building model.

Abstract: Imagery is used to identify architectural elements that have known architectural patterns. Feature sets associated with a surface and architectural elements in a building model image are compared with known architectural standards of materials to determine the surface building materials and architectural details of a textured building model. In addition, specific texture patterns can assist final material selections for a repair/replacement.

Abstract: A system and method is provided for identifying error and rescaling and constructing or reconstructing a multi-dimensional (e.g., 3D) building model using street-level imagery. Street-level imagery is used to identify architectural elements that have known architectural standard dimensions. Dimensional measurements of architectural elements in the multi-dimensional building model (poorly scaled) are compared with known architectural standard dimensions to rescale and construct/reconstruct an accurate multi-dimensional building model.

Abstract: A system is provided including a database that ingests data from disparate image sources, with a variety of image metadata types and qualities, and manages images geospatially through the creation and continued refinement of camera solutions for each data object included. These camera solutions are calculated and refined by the database as additional data enters the system that could affect the solutions, through a combination of the application of image metadata towards image processing methods and the use of optical-only computer vision techniques. The database continually generates data quality metrics and relevant imagery and geometry analytics, which drive future collection tasking, system analytics, and human quality control requirements.

Abstract: A method of operating a three-dimensional (3D) map system including: receiving an image and a geo-location tag of the image; determining a building model for a physical building corresponding to an object captured in the image based on the geo-location tag; mapping, on a region-by-region basis, the image to a stored facade of the building model; and mapping, on a pixel-by-pixel basis, the image to the stored facade of the building model for displaying the image as a new facade of the building.