Hover, Inc.

Shaohui Sun

Ioannis Pavlidis

Adam J Altman

Vineet Bhatawadekar

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 for generating three dimensional geometry

A system and method is provided for generating textured 3D building models from ground-level imagery. Ground-level images for the sides/corners of building objects are collected for identification of key architectural features, corresponding key fa&#xe7;ade geometry planes, and generation of a 3D building fa&#xe7;ade geometry. The 3D building model is properly geo-positioned, scaled and textured.

Generating multi-dimensional building models with ground level images

Systems and methods are described for adjusting planar geometry derived from point cloud data associated with a building object by identifying major aspects like vertices and edges of the underlying structure within the point cloud and adjusting an average planar fit for simplified geometries created from the point cloud. Combining the planar geometry or point cloud with orthogonal or street level views improves accuracy and use cases of the planar geometry.

Systems and methods for generating planar geometry

A system and method is provided for generating textured building models from wirelessly captured ground-level imagery. Ground-level images of facades of building objects are collected for identification of geometry planes and generation of building fa&#xe7;ade geometry. The 3D building model is properly geo-positioned, scaled and textured.

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.

Scaling in a multi-dimensional building model

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.

Scale error correction in a multi-dimensional model

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.

Building material classifications from imagery

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.

A system and method is provided for generating textured 3D building models from ground-level and orthogonal imagery. Ground-level images for the sides of building objects are collected to form a 3D dense point cloud for identification of key architectural features, corresponding key fa&#xe7;ade geometry planes, and generation of a 3D building fa&#xe7;ade geometry. Orthogonal images are correlated to the 3D building model providing a properly geo-positioned, scaled and textured 3D building model.

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Mountain View, CA, United States of America

Shaohui Sun