Hover Inc.

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.

Techniques are described for identifying correspondences between images to generate a fundamental matrix for the camera positions related to the images. The resultant fundamental matrix enables epipolar geometry to correlate common features among the images. Correspondences are identified by confirming feature matches across images by applying a homography to data representing features across images. Further techniques are described herein for generating a representation of a boundary of a feature of a structure based on a digital image. In one or more embodiments, generating a representation of a boundary of a particular feature in a digital image comprises determining a portion of the image that corresponds to the structure, and determining a portion of the image that corresponds to the particular feature. One more vanishing points are associated with the portion of the image corresponding to the particular feature. The one or more vanishing points are used to generate a set of bounding lines for the particular feature, based on which the boundary indicator for the feature is generated.

Systems and methods are disclosed for directed image capture of a subject of interest, such as a physical building. Directed image capture can produce higher quality images such as content more centrally located within an image frame (or an associated viewing device or other display), higher quality images have greater value for subsequent uses of captured images such as for information extraction or model reconstruction. Graphical guide(s) overlaid within an image frame can facilitate quality assessments for the content or the image frame itself, such as for pixel distance of the subject of interest to a centroid of the image frame (or an associated viewing device or other display), 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.

A method renders photorealistic images in a web browser. The method is performed at a computing device having a general purpose processor and a graphics processing unit (GPU). The method includes obtaining an environment map and images of an input scene. The method also includes computing textures for the input scene including by encoding an acceleration structure of the input scene. The method further includes transmitting the textures to shaders executing on a GPU. The method includes generating samples of the input scene, by performing at least one path tracing algorithm on the GPU, according to the textures. The method also includes lighting or illuminating a sample of the input scene using the environment map, to obtain a lighted scene, and tone mapping the lighted scene. The method includes drawing output on a canvas, in the web browser, based on the tone-mapped scene to render the input scene.

Systems and methods are described for creating three dimensional models of building objects by creating a point cloud from a plurality of input images, defining edges of the building object's surfaces represented by the point cloud, creating simplified geometries of the building object's surfaces and constructing a building model based on the simplified geometries. Input images may include ground, orthographic, or oblique images. The resultant model may be scaled according to correlation with select image types and textured.

Systems and methods are described for creating three dimensional models of building objects by creating a point cloud from a plurality of input images, defining edges of the building object's surfaces represented by the point cloud, creating simplified geometries of the building object's surfaces and constructing a building model based on the simplified geometries. Input images may include ground, orthographic, or oblique images. The resultant model may be scaled according to correlation with select image types and textured.

Disclosed are techniques for enhancing two-dimensional (2D) image capture of subjects (e.g., a physical structure, such as a residential building) to maximize the feature correspondences available for three-dimensional (3D) model reconstruction. More specifically, disclosed is a computer-vision network configured to provide viewfinder interfaces and analyses to guide the improved capture of an intended subject for specified purposes. Additionally, the computer-vision network can be configured to generate a metric representing a quality of feature correspondences between images of a complete set of images used for reconstructing a 3D model of a physical structure. The computer-vision network can also be configured to generate feedback at or before image capture time to guide improvements to the quality of feature correspondences between a pair of images.

Methods, storage media, and systems for measuring an angle of a roof facet are disclosed. Exemplary implementations may include initiating a flight path for an image capture device, the flight path including, at successively greater heights, a starting position, a calibration position, and an orthographic position above the roof facet. A first fiducial is detected as or at the calibration position and a second fiducial is detected concurrent with movement of the image capture device along the flight path towards the orthographic position. An elevation change of the image capture device is measured between the first fiducial and second fiducial. An orthographic image of the roof facet is captured from the orthographic position. An outline of the roof facet is generated from the orthographic image. A pitch of the roof is calculated from the outline of the roof facet and the elevation change.

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.

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.