Abstract: Systems and methods are disclosed for guiding image capture of a subject by determining a location of the subject and presenting on a display graphical guides representative of perspective views of the subject to be captured. Images of the subject may then be captured and additional graphical guides are presented to the user for display for additional images to be captured. Images may be captured in a predetermined sequence of graphical guides or responsive to a user input or camera information. Captured images may be uploaded to a system for additional processing.

Abstract: A computer system trains a machine learning model to estimate a real-world measurement of a feature of a structure. The machine learning model is trained using a plurality of digital image sets, wherein each image set depicts a particular structure, and a plurality of measurements, wherein each measurement is a measurement of a feature of a particular structure. After the machine learning model is trained, it is used to estimate a measurement of a feature of a particular structure depicted in a particular image set.

Abstract: An image capture system provides automated prompts for aiding a user in capturing images for use in 3D model creation. While a user is preparing to capture an image, the system provides visual indications that indicate whether a quality-based condition is satisfied. Based on the visual indications, a user can determine whether an image, if captured, would likely be suitable for use in creating a 3D model. Determining if the quality-based condition is satisfied may include monitoring output generated by one or more sensors and comparing the output against a threshold value. Additionally, the system may analyze the visual content or metadata associated with an image to determine if the quality-based condition is satisfied and request user input to further identify certain image features that were identified by the system.

Abstract: A process for creating, responsive to a desired analysis, estimate information from received imagery by determining whether the imagery meets a minimum criterion for creating a multi-dimensional model that can address the desired analysis and building an aggregate set of images meeting the minimum criterion from which a multi-dimensional model is then built and an estimate responsive to the desired analysis is derived. The multi-dimensional model, and the responsive estimate, may be refined as additional images are provided to the aggregate set. Desired analyses may include dimensions such as square footage of a roof for building objects.

Abstract: A computer system trains a machine learning model to estimate a real-world measurement of a feature of a structure. The machine learning model is trained using a plurality of digital image sets, wherein each image set depicts a particular structure, and a plurality of measurements, wherein each measurement is a measurement of a feature of a particular structure. After the machine learning model is trained, it is used to estimate a measurement of a feature of a particular structure depicted in a particular image set.

Abstract: System and method are provided for scaling a 3-D representation of a building structure. The method includes obtaining images of the building structure, including non-camera anchors. The method also includes identifying reference poses for images based on the non-camera anchors. The method also includes obtaining world map data including real-world poses for the images. The method also includes selecting candidate poses from the real-world poses based on corresponding reference poses. The method also includes calculating a scaling factor for a 3-D representation of the building structure based on correlating the reference poses with the selected candidate poses. Some implementations use structure from motion techniques or LiDAR, in addition to augmented reality frameworks, for scaling the 3-D representations of the building structure. In some implementations, the world map data includes environmental data, such as illumination data, and the method includes generating or displaying the 3-D representation.

Abstract: A computer system generates an outline of a roof of a structure based on a set of lateral images depicting the structure. For each image in the set of lateral images, one or more rooflines corresponding to the roof of the structure are determined. The computer system determines how the rooflines connect to one another. Based on the determination, the rooflines are connected to generate an outline of the roof.

Abstract: A computer system generates an outline of a roof of a structure based on a set of lateral images depicting the structure. For each image in the set of lateral images, one or more rooflines corresponding to the roof of the structure are determined. The computer system determines how the rooflines connect to one another. Based on the determination, the rooflines are connected to generate an outline of the roof.

Abstract: An image capture system provides automated prompts for aiding a user in capturing images for use in 3D model creation. While a user is preparing to capture an image, the system provides visual indications that indicate whether a quality-based condition is satisfied. Based on the visual indications, a user can determine whether an image, if captured, would likely be suitable for use in creating a 3D model. Determining if the quality-based condition is satisfied may include monitoring output generated by one or more sensors and comparing the output against a threshold value. Additionally, the system may analyze the visual content or metadata associated with an image to determine if the quality-based condition is satisfied and request user input to further identify certain image features that were identified by the system.

Abstract: System and method are provided for scaling a 3-D representation of a building structure. The method includes obtaining images of the building structure, including non-camera anchors. The method also includes identifying reference poses for images based on the non-camera anchors. The method also includes obtaining world map data including real-world poses for the images. The method also includes selecting candidate poses from the real-world poses based on corresponding reference poses. The method also includes calculating a scaling factor for a 3-D representation of the building structure based on correlating the reference poses with the selected candidate poses. Some implementations use structure from motion techniques or LiDAR, in addition to augmented reality frameworks, for scaling the 3-D representations of the building structure. In some implementations, the world map data includes environmental data, such as illumination data, and the method includes generating or displaying the 3-D representation.

Abstract: An image capture system provides automated prompts for aiding a user in capturing images for use in 3D model creation. While a user is preparing to capture an image, the system provides visual indications that indicate whether a quality-based condition is satisfied. Based on the visual indications, a user can determine whether an image, if captured, would likely be suitable for use in creating a 3D model. Determining if the quality-based condition is satisfied may include monitoring output generated by one or more sensors and comparing the output against a threshold value. Additionally, the system may analyze the visual content or metadata associated with an image to determine if the quality-based condition is satisfied and request user input to further identify certain image features that were identified by the system.

Abstract: A computer system maintains structure data indicating geometrical constraints for each structure category of a plurality of structure categories. The computer system generates a virtual 3D representation of a structure based on a set of images depicting the structure. For each image in the set of images, one or more landmarks are identified. Based on the landmarks, a candidate structure category is selected. The virtual 3D representation is generated based on the geometrical constraints of the candidate structure category and the landmarks identified in the set of images.

Abstract: Systems and methods are disclosed for directed image capture of a subject of interest, such as a home. Directed image capture can produce higher quality images such as more centrally located within a display and/or viewfinder of an image capture device, higher quality images have greater value for subsequent uses of captured images such as for information extraction or model reconstruction. Graphical guide(s) facilitate content placement for certain positions and quality assessments for the content of interest can be calculated such as for pixel distance of the content of interest to a centroid of the display or viewfinder, or the effect of obscuring objects. Quality assessments can further include instructions for improving the quality of the image capture for the content of interest.

Abstract: A computer system maintains structure data indicating geometrical constraints for each structure category of a plurality of structure categories. The computer system generates a virtual 3D representation of a structure based on a set of images depicting the structure. For each image in the set of images, one or more landmarks are identified. Based on the landmarks, a candidate structure category is selected. The virtual 3D representation is generated based on the geometrical constraints of the candidate structure category and the landmarks identified in the set of images.

Abstract: Systems and methods are disclosed for adjusting plane positions in multi-dimensional models. Disclosed is moving a plane associated with an architectural element based on a scale and a translation positional error, wherein the scaled is determined based on the architectural element, and the translation position error is based on a position of the architectural element, and reconstructing the multi-dimensional building model based on the moved plane.

Abstract: Systems and methods are disclosed for directed image capture of a subject of interest, such as a home. Directed image capture can produce higher quality images such as more centrally located within a display and/or viewfinder of an image capture device, higher quality images have greater value for subsequent uses of captured images such as for information extraction or model reconstruction. Graphical guide(s) facilitate content placement for certain positions and quality assessments for the content of interest can be calculated such as for pixel distance of the content of interest to a centroid of the display or viewfinder, or the effect of obscuring objects. Quality assessments can further include instructions for improving the quality of the image capture for the content of interest.

Abstract: Visualizing three dimensional content is complicated by display platforms capable of more degrees of freedom to display the content than interface tools have to navigate that content. Disclosed are methods and systems for displaying select portions of the content and generating virtual camera positions with associated look angles for the select portions, such as planar geometries of a three dimensional building, thereby constraining the degrees of freedom for improved navigation through views of the content. Look angles can be associated with axes of the content and fields of view.

Abstract: A computer system generates an outline of a roof of a structure based on a set of lateral images depicting the structure. For each image in the set of lateral images, one or more rooflines corresponding to the roof of the structure are determined. The computer system determines how the rooflines connect to one another. Based on the determination, the rooflines are connected to generate an outline of the roof.

Abstract: Systems and methods are disclosed for guiding image capture of a subject by determining a location of the subject and presenting on a display graphical guides representative of perspective views of the subject to be captured. Images of the subject may then be captured and additional graphical guides are presented to the user for display for additional images to be captured. Images may be captured in a predetermined sequence of graphical guides or responsive to a user input or camera information. Captured images may be uploaded to a system for additional processing.

Abstract: System and method are provided for scaling a 3-D representation of a building structure. The method includes obtaining images of the building structure, including non-camera anchors. The method also includes identifying reference poses for images based on the non-camera anchors. The method also includes obtaining world map data including real-world poses for the images. The method also includes selecting candidate poses from the real-world poses based on corresponding reference poses. The method also includes calculating a scaling factor for a 3-D representation of the building structure based on correlating the reference poses with the selected candidate poses. Some implementations use structure from motion techniques or LiDAR, in addition to augmented reality frameworks, for scaling the 3-D representations of the building structure. In some implementations, the world map data includes environmental data, such as illumination data, and the method includes generating or displaying the 3-D representation.