Abstract: User interface systems and methods for roof estimation are described. Example embodiments include a roof estimation system that provides a user interface configured to facilitate roof model generation based on one or more aerial images of a building roof. In one embodiment, roof model generation includes image registration, image lean correction, roof section pitch determination, wire frame model construction, and/or roof model review. The described user interface provides user interface controls that may be manipulated by an operator to perform at least some of the functions of roof model generation. The user interface is further configured to concurrently display roof features onto multiple images of a roof. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: User interface systems and methods for roof estimation are described. Example embodiments include a roof estimation system that provides a user interface configured to facilitate roof model generation based on one or more aerial images of a building roof. In one embodiment, roof model generation includes image registration, image lean correction, roof section pitch determination, wire frame model construction, and/or roof model review. The described user interface provides user interface controls that may be manipulated by an operator to perform at least some of the functions of roof model generation. In one embodiment, the user interface provides user interface controls that facilitate the determination of pitch of one or more sections of a building roof. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: Automatic roof identification systems and methods are described. Example embodiments include a roof estimation system configured to automatically detect a roof in a target image of a building having a roof. In one embodiment, automatically detecting a roof in a target image includes training one or more artificial intelligence systems to identify likely roof sections of an image. The artificial intelligence systems are trained on historical image data or an operator-specified region of interest within the target image. Then, a likely outline of the roof in the target image can be determined based on the trained artificial intelligence systems. The likely roof outline can be used to generate a roof estimate report. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: The present disclosure proposes computer-based systems and methods for determining, for an application, the most relevant subset of images across a number of sources of images by identifying images over multiple image providers, aggregating image collection over those images that are candidates for use, evaluating candidate images based on comparing image metadata against customizable image preference criteria, and producing a set of images to be selected either by a user or by a computer for use in the application.

Abstract: Automatic roof identification systems and methods are described. Example embodiments include a roof estimation system configured to automatically detect a roof in a target image of a building having a roof. In one embodiment, automatically detecting a roof in a target image includes training one or more artificial intelligence systems to identify likely roof sections of an image. The artificial intelligence systems are trained on historical image data or an operator-specified region of interest within the target image. Then, a likely outline of the roof in the target image can be determined based on the trained artificial intelligence systems. The likely roof outline can be used to generate a roof estimate report. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: User interface systems and methods for roof estimation are described. Example embodiments include a roof estimation system that provides a user interface configured to facilitate roof model generation based on one or more aerial images of a building roof. In one embodiment, roof model generation includes image registration, image lean correction, roof section pitch determination, wire frame model construction, and/or roof model review. The described user interface provides user interface controls that may be manipulated by an operator to perform at least some of the functions of roof model generation. In one embodiment, the user interface provides user interface controls that facilitate the determination of pitch of one or more sections of a building roof. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: User interface systems and methods for roof estimation are described. Example embodiments include a roof estimation system that provides a user interface configured to facilitate roof model generation based on one or more aerial images of a building roof. In one embodiment, roof model generation includes image registration, image lean correction, roof section pitch determination, wire frame model construction, and/or roof model review. The described user interface provides user interface controls that may be manipulated by an operator to perform at least some of the functions of roof model generation. The user interface is further configured to concurrently display roof features onto multiple images of a roof. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: Systems and methods are disclosed for a property management system that runs on a smartphone and allows users to identify and track information on one or more properties and to receive property updates from the server. Systems and methods are also disclosed that use the orientation of and images captured by a smartphone camera to identify a facet of an object and to determine its pitch.

Abstract: User interface systems and methods for roof estimation are described. Example embodiments include a roof estimation system that provides a user interface configured to facilitate roof model generation based on one or more aerial images of a building roof. In one embodiment, roof model generation includes image registration, image lean correction, roof section pitch determination, wire frame model construction, and/or roof model review. The described user interface provides user interface controls that may be manipulated by an operator to perform at least some of the functions of roof model generation. The user interface is further configured to concurrently display roof features onto multiple images of a roof. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: User interface systems and methods for roof estimation are described. Example embodiments include a roof estimation system that provides a user interface configured to facilitate roof model generation based on one or more aerial images of a building roof. In one embodiment, roof model generation includes image registration, image lean correction, roof section pitch determination, wire frame model construction, and/or roof model review. The described user interface provides user interface controls that may be manipulated by an operator to perform at least some of the functions of roof model generation. In one embodiment, the user interface provides user interface controls that facilitate the determination of pitch of one or more sections of a building roof. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: System and methods for performing a risk management assessment of a property using at least aerial imagery of the property and additional data about the property that is evaluated against risk management criteria. Data acquired through aerial imagery includes identifying buildings and floor area of the buildings, condition of the buildings including roof and exterior walls, and identifying other property hazards. Additional data may include property information coming from multiple sources including city and County governments, contractors and insurance companies. The resulting risk management assessment may be used to settle insurance claims and to determine insurance products and premium rates offered on the property.

Abstract: A system generates an estimated floor area measurement of a building based on the calculated estimated total roof area of the roof of the building. This is based on a correlation between the size of the building roof and the size of the building. Typically, the floor area of a single full floor of the building is roughly the size of the roof of the building if the roof were flat with no slope. This in effect is turning the roof into a floor to generate estimated floor area. With additional adjustments to area measurements to account for multiple floors, roof overhang, wall width, internal building features such as walls and staircases, and/or obstructed views of the building in the aerial image(s), etc., an even more accurate floor area estimation may be generated.

Abstract: Methods and systems for roof estimation are described. Example embodiments include a roof estimation system, which generates and provides roof estimate reports annotated with indications of the size, geometry, pitch and/or orientation of the roof sections of a building. Generating a roof estimate report may be based on one or more aerial images of a building. In some embodiments, generating a roof estimate report of a specified building roof may include generating a three-dimensional model of the roof, and generating a report that includes one or more views of the three-dimensional model, the views annotated with indications of the dimensions, area, and/or slope of sections of the roof. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: Automatic roof identification systems and methods are described. Example embodiments include a roof estimation system configured to automatically detect a roof in a target image of a building having a roof. In one embodiment, automatically detecting a roof in a target image includes training one or more artificial intelligence systems to identify likely roof sections of an image. The artificial intelligence systems are trained on historical image data or an operator-specified region of interest within the target image. Then, a likely outline of the roof in the target image can be determined based on the trained artificial intelligence systems. The likely roof outline can be used to generate a roof estimate report. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: Methods and systems for roof estimation are described. Example embodiments include a roof estimation system, which generates and provides roof estimate reports annotated with indications of the size, geometry, pitch and/or orientation of the roof sections of a building. Generating a roof estimate report may be based on one or more aerial images of a building. The slope and orientation images are typically oblique perspective views and top plan views of the buildings in the area. In some embodiments, generating a roof estimate report of a specified building roof may include generating a three-dimensional model of the roof, and generating a report that includes one or more views of the three-dimensional model, the views annotated with indications of the dimensions, area, and/or slope of sections of the roof. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Abstract: A wall area estimation system generates an estimated wall area measurement of a building based on the received roof measurements (e.g., those generated by, received from or found in a three-dimensional model of the roof) and a reference distance. The reference distance is a measurement indicative of a distance between the roof and a model ground surface placed on an image of the building where the walls of the building meet the ground. This reference distance may be used to determine how for down to extend the walls of the building (e.g., to a ground level) when building a three-dimensional digital model of the building to aid in generating wall area measurements. The resulting wall measurements, roof measurements, measurements of areas missing from the wall used to generate a wall estimate report, or a combined roof and wall estimate report including various different identifiers indicating the different features and measurements based on the three-dimensional model.

Abstract: A system generates an estimated floor area measurement of a building based on the calculated estimated total roof area of the roof of the building. This is based on a correlation between the size of the building roof and the size of the building. Typically, the floor area of a single full floor of the building is roughly the size of the roof of the building if the roof were flat with no slope. This in effect is turning the roof into a floor to generate estimated floor area. With additional adjustments to area measurements to account for multiple floors, roof overhang, wall width, internal building features such as walls and staircases, and/or obstructed views of the building in the aerial image(s), etc., an even more accurate floor area estimation may be generated.

Abstract: A system that allows the remote measurement of the size, geometry, pitch and orientation of the roof sections of a building and then uses the information to provide an estimate to repair or replace the roof, or to install equipment thereon. The system includes an aerial image file database that shows aerial images of buildings in a designated area according to address. The slope and orientation images are typically oblique perspective views and top plan views of the buildings in the area. The system also includes an image analysis and calibration feature that enables the viewer to closely estimate the size, geometry and orientation of the building's roof sections. The information can then be used to prepare a cost estimate for the repair or replacement of the roof or installation of roof equipment.

Abstract: A system generates an estimated floor area measurement of a building based on the calculated estimated total roof area of the roof of the building. This is based on a correlation between the size of the building roof and the size of the building. Typically, the floor area of a single full floor of the building is roughly the size of the roof of the building if the roof were flat with no slope. This in effect is turning the roof into a floor to generate estimated floor area. With additional adjustments to area measurements to account for multiple floors, roof overhang, wall width, internal building features such as walls and staircases, and/or obstructed views of the building in the aerial image(s), etc., an even more accurate floor area estimation may be generated.

Abstract: A wall area estimation system generates an estimated wall area measurement of a building based on the received roof measurements (e.g., those generated by, received from or found in a three dimensional model of the roof) and a reference distance. The reference distance is a measurement indicative of a distance between a reference point on the roof and a ground surface. This reference distance may be used to determine how for down to extend the walls of the building (e.g., to a ground level) when building a three dimensional digital model of the building to aid in generating wall area measurements. The resulting wall measurements, roof measurements, measurements of areas missing from the wall used to generate a wall estimate report, or a combined roof and wall estimate report including various different identifiers indicating the different features and measurements based on the three dimensional model.