Abstract: A system and method for construction estimation using aerial images is provided. The system receives at least one aerial image of a building. An estimation engine processes the aerial image at a plurality of angles to automatically identify a plurality (e.g., perimeter and interior) lines in the image corresponding to a plurality of features of a roof the building. The estimation engine allows users to generate two-dimensional and three-dimensional models of the roof by automatically delineating various roof features, and generates a report including information about the roof of the building.

Abstract: Systems and methods for rapidly developing annotated computer models of structures and properties is provided. The system generates three-dimensional (3D) models of structures and property using a wide variety of digital imagery, and/or can process existing 3D models created by other systems. The system processes the 3D models to automatically identify candidate objects within the 3D models that may be suitable for annotation, such as roof faces, chimneys, windows, gutters, etc., using computer vision techniques to automatically identify such objects. Once the candidate objects have been identified, the system automatically generates user interface screens which gather relevant information related to the candidate objects, so as to rapidly obtain, associate, and store annotation information related to the candidate objects.

Abstract: A system and method for construction estimation using aerial images is provided. The system receives at least one aerial image of a building. An estimation engine processes the aerial image at a plurality of angles to automatically identify a plurality (e.g., perimeter and interior) lines in the image corresponding to a plurality of features of a roof the building. The estimation engine allows users to generate two-dimensional and three-dimensional models of the roof by automatically delineating various roof features, and generates a report including information about the roof of the building.

Abstract: Computer vision systems and methods for generating building models using three-dimensional sensing and augmented reality (AR) techniques are provided. Image frames including images of a structure to be modeled are captured by a camera of a mobile device such as a smart phone, as well as three-dimensional data corresponding to the image frames. An object of interest, such as a structural feature of the building, is detected using both the image frames and the three-dimensional data. An AR icon is determined based upon the type of object detected, and is displayed on the mobile device superimposed on the image frames. The user can manipulate the AR icon to better fit or match the object of interest in the image frames, and can capture the object of interest using a capture icon displayed on the display of the mobile device.

Abstract: A system and method for generating a parametric model of a roof structure comprising a processor in communication with a memory. The system receives a plurality of parameters of each roof component composing the roof structure and performs a geometry creation based on the received plurality of parameters. The system generates a constrained three-dimensional geometry based on an output of the geometry creation, and displays a three-dimensional model of the roof structure based on the constrained three-dimensional geometry.

Abstract: Systems and methods for detecting, extracting, and categorizing structure data from aerial imagery following a major weather event are provided. The system processes digital images and weather data to automatically detect, extract, and categorize structure data following a major weather event. After receiving an indication of a region of interest (“ROI”) from a user, the system retrieves weather mapping data for the ROI and retrieves information related to attributes of structures within the ROI from a machine learning subsystem. The system then cross-references the property data, the weather data, and the structure attributes and assigns a risk rating to the structures within the ROI. Finally, the system generates and delivers a data package to the user.

Abstract: Computer vision systems and methods for generating building models using three-dimensional sensing and augmented reality (AR) techniques are provided. Image frames including images of a structure to be modeled are captured by a camera of a mobile device such as a smart phone, as well as three-dimensional data corresponding to the image frames. An object of interest, such as a structural feature of the building, is detected using both the image frames and the three-dimensional data. An AR icon is determined based upon the type of object detected, and is displayed on the mobile device superimposed on the image frames. The user can manipulate the AR icon to better fit or match the object of interest in the image frames, and can capture the object of interest using a capture icon displayed on the display of the mobile device.

Abstract: Computer vision systems and methods for generating building models using three-dimensional sensing and augmented reality (AR) techniques are provided. Image frames including images of a structure to be modeled are captured by a camera of a mobile device such as a smart phone, as well as three-dimensional data corresponding to the image frames. An object of interest, such as a structural feature of the building, is detected using both the image frames and the three-dimensional data. An AR icon is determined based upon the type of object detected, and is displayed on the mobile device superimposed on the image frames. The user can manipulate the AR icon to better fit or match the object of interest in the image frames, and can capture the object of interest using a capture icon displayed on the display of the mobile device.

Abstract: Computer vision systems and methods for generating building models using three-dimensional sensing and augmented reality (AR) techniques are provided. Image frames including images of a structure to be modeled are captured by a camera of a mobile device such as a smart phone, as well as three-dimensional data corresponding to the image frames. An object of interest, such as a structural feature of the building, is detected using both the image frames and the three-dimensional data. An AR icon is determined based upon the type of object detected, and is displayed on the mobile device superimposed on the image frames. The user can manipulate the AR icon to better fit or match the object of interest in the image frames, and can capture the object of interest using a capture icon displayed on the display of the mobile device.

Abstract: Systems and methods for detecting, extracting, and categorizing structure data from aerial imagery following a major weather event are provided. The system processes digital images and weather data to automatically detect, extract, and categorize structure data following a major weather event. After receiving an indication of a region of interest (“ROI”) from a user, the system retrieves weather mapping data for the ROI and retrieves information related to attributes of structures within the ROI from a machine learning subsystem. The system then cross-references the property data, the weather data, and the structure attributes and assigns a risk rating to the structures within the ROI. Finally, the system generates and delivers a data package to the user.

Abstract: Computer vision systems and methods for generating building models using three-dimensional sensing and augmented reality (AR) techniques are provided. Image frames including images of a structure to be modeled are captured by a camera of a mobile device such as a smart phone, as well as three-dimensional data corresponding to the image frames. An object of interest, such as a structural feature of the building, is detected using both the image frames and the three-dimensional data. An AR icon is determined based upon the type of object detected, and is displayed on the mobile device superimposed on the image frames. The user can manipulate the AR icon to better fit or match the object of interest in the image frames, and can capture the object of interest using a capture icon displayed on the display of the mobile device.

Abstract: A system and method for construction estimation using aerial images is provided. The system receives at least one aerial image of a building. An estimation engine processes the aerial image at a plurality of angles to automatically identify a plurality (e.g., perimeter and interior) lines in the image corresponding to a plurality of features of a roof the building. The estimation engine allows users to generate two-dimensional and three-dimensional models of the roof by automatically delineating various roof features, and generates a report including information about the roof of the building.

Abstract: A system and method for construction estimation using aerial images is provided. The system receives at least one aerial image of a building. An estimation engine processes the aerial image at a plurality of angles to automatically identify a plurality (e.g., perimeter and interior) lines in the image corresponding to a plurality of features of a roof the building. The estimation engine allows users to generate two-dimensional and three-dimensional models of the roof by automatically delineating various roof features, and generates a report including information about the roof of the building.

Abstract: A system and method for construction estimation using aerial images is provided. The system receives at least one aerial image of a building. An estimation engine processes the aerial image at a plurality of angles to automatically identify a plurality (e.g., perimeter and interior) lines in the image corresponding to a plurality of features of a roof the building. The estimation engine allows users to generate two-dimensional and three-dimensional models of the roof by automatically delineating various roof features, and generates a report including information about the roof of the building.

Abstract: Systems and methods for rapidly developing annotated computer models of structures and properties is provided. The system generates three-dimensional (3D) models of structures and property using a wide variety of digital imagery, and/or can process existing 3D models created by other systems. The system processes the 3D models to automatically identify candidate objects within the 3D models that may be suitable for annotation, such as roof faces, chimneys, windows, gutters, etc., using computer vision techniques to automatically identify such objects. Once the candidate objects have been identified, the system automatically generates user interface screens which gather relevant information related to the candidate objects, so as to rapidly obtain, associate, and store annotation information related to the candidate objects.

Abstract: Systems and methods for rapidly developing annotated computer models of structures and properties is provided. The system generates three-dimensional (3D) models of structures and property using a wide variety of digital imagery, and/or can process existing 3D models created by other systems. The system processes the 3D models to automatically identify candidate objects within the 3D models that may be suitable for annotation, such as roof faces, chimneys, windows, gutters, etc., using computer vision techniques to automatically identify such objects. Once the candidate objects have been identified, the system automatically generates user interface screens which gather relevant information related to the candidate objects, so as to rapidly obtain, associate, and store annotation information related to the candidate objects.

Abstract: Computer vision systems and methods for generating building models using three-dimensional sensing and augmented reality (AR) techniques are provided. Image frames including images of a structure to be modeled are captured by a camera of a mobile device such as a smart phone, as well as three-dimensional data corresponding to the image frames. An object of interest, such as a structural feature of the building, is detected using both the image frames and the three-dimensional data. An AR icon is determined based upon the type of object detected, and is displayed on the mobile device superimposed on the image frames. The user can manipulate the AR icon to better fit or match the object of interest in the image frames, and can capture the object of interest using a capture icon displayed on the display of the mobile device.

Abstract: A system and method for construction estimation using aerial images is provided. The system receives at least one aerial image of a building. An estimation engine processes the aerial image at a plurality of angles to automatically identify a plurality (e.g., perimeter and interior) lines in the image corresponding to a plurality of features of a roof the building. The estimation engine allows users to generate two-dimensional and three-dimensional models of the roof by automatically delineating various roof features, and generates a report including information about the roof of the building.

Abstract: A system and method for construction estimation using aerial images is provided. The system receives at least one aerial image of a building. An estimation engine processes the aerial image at a plurality of angles to automatically identify a plurality (e.g., perimeter and interior) lines in the image corresponding to a plurality of features of a roof the building. The estimation engine allows users to generate two-dimensional and three-dimensional models of the roof by automatically delineating various roof features, and generates a report including information about the roof of the building.

Abstract: Systems and methods for detecting, extracting, and categorizing structure data from aerial imagery following a major weather event are provided. The system processes digital images and weather data to automatically detect, extract, and categorize structure data following a major weather event. After receiving an indication of a region of interest (“ROI”) from a user, the system retrieves weather mapping data for the ROI and retrieves information related to attributes of structures within the ROI from a machine learning subsystem. The system then cross-references the property data, the weather data, and the structure attributes and assigns a risk rating to the structures within the ROI. Finally, the system generates and delivers a data package to the user.