Mftb Holdco, Inc.

Zillow, Inc.

Zillow Group, Inc.

Yuguang Li

Ivaylo Boyadzhiev

Will Adrian Hutchcroft

Romualdo T Impas

Pierre Moulon

Christopher J Buehler

Naji Khosravan

Lambert E Wixson

Li Guan

Joshuah Vincent

Manjunath Narayana

Sing Bing Kang

Michael P Caputo

Gregory Joseph Doerr

John W Lambert

Joshua Weisberg

Yujie Li

Zhiqiang Wan

Grant Gingell

Negar Nejatishahidin

Techniques are described for automated operations to analyze visual data from images acquired in multiple rooms of a building to generate multiple types of building information (e.g., to include a floor plan for the building), such as by simultaneously or otherwise concurrently analyzing groups of three or more images having at least pairwise visual overlap between pairs of those images to determine information that includes global inter-image pose and structural element locations, and for subsequently using the generated building information in one or more further automated manners, with the building information generation further performed in some cases without having or using information from any distance-measuring devices about distances from an image's acquisition location to walls or other objects in the surrounding room.

Automated inter-image analysis of multiple building images for building floor plan generation

Techniques are described for using computing devices to perform automated operations related to providing visual information of multiple types in an integrated manner about a building or other defined area. The techniques may include generating and presenting a GUI (graphical user interface) on a client device that includes a computer model of the building's interior with one or more first types of information (e.g., in a first pane of the GUI), and simultaneously presenting other types of related information about the building interior (e.g., in additional separate GUI pane(s)) that is coordinated with the first type(s) of information being currently displayed. The computer model may be a 3D (three-dimensional) or 2.5D representation generated after the house is built and showing the actual house's interior (e.g., walls, furniture, etc.), and may be displayed to a user of a client computing device in a displayed GUI with various user-selectable controls.

Presenting building information using video and building models

Techniques are described for computing devices to perform automated operations related to using images acquired in a building as part of an automated generation process of a floor plan or other mapping information for the building, in some cases without using depth information from depth-sensing equipment about distances from the images' acquisition locations to objects in the surrounding building, and for subsequent use in further automated manners, such as controlling navigation of mobile devices and/or for display to end users in a corresponding graphical user interface. The automated analysis and assessment of the building images may, for example, include incrementally generating partial versions of the mapping information, determining acquisition instructions related to further acquisition of additional images and/or other types of data (e.g., to reduce uncertainty associated with portions of the partial mapping information or otherwise obtain missing data), and providing corresponding guidance in or more manners.

Automated tools for incremental generation of building mapping information

Techniques are described for automated operations to analyze visual data from images acquired in multiple rooms of a building to generate one or more types of building information (e.g., global inter-image pose data, a floor plan for the building, etc.), such as by simultaneously or otherwise concurrently analyzing groups of three or more images having at least pairwise visual overlap between pairs of those images to determine information that includes global inter-image pose and structural element locations, and for subsequently using the generated building information in one or more further automated manners, with the building information generation further performed in some cases without having or using information from any distance-measuring devices about distances from an image's acquisition location to walls or other objects in the surrounding room.

Automated inter-image analysis of multiple building images for building information determination

Techniques are described for automated operations to analyze visual data from images acquired in multiple rooms of a building to generate multiple types of building information (e.g., to include a floor plan for the building), such as by using a trained neural network to jointly generate the multiple types of building information by combining visual data from pairs of the images, and for subsequently using the generated building information in one or more further automated manners, with the building information generation further performed in some cases without having or using information from any distance-measuring devices about distances from an image's acquisition location to walls or other objects in the surrounding room. The automated operations may include generating some types of building information with respect to each image pixel column, and other types of building information by combining data from both images of a pair.

Automated building information determination using inter-image analysis of multiple building images

Techniques are described for using computing devices to perform automated operations involved in analysis of images acquired in a defined area, as part of generating mapping information of the defined area for subsequent use (e.g., for controlling navigation of devices, for display on client devices in corresponding GUIs, etc.). The defined area may include an interior of a multi-room building, and the generated information including a floor map of the building, such as from an analysis of multiple 360° spherical panorama images acquired at various viewing locations within the building (e.g., using an image acquisition device with a spherical camera having one or more fisheye lenses to capture a panorama image that extends 360 degrees around a vertical axis)—the generating may be further performed without detailed information about distances from the images' viewing locations to objects in the surrounding building.

Automated tools for generating mapping information for buildings

Presenting building information using building models

Techniques are described for computing devices to perform automated operations related to using images acquired in a building as part of generating a floor plan for the building, in some cases without using depth information from depth-sensing equipment about distances from the images' acquisition locations to objects in the surrounding building, and for subsequent use in further automated manners, such as controlling navigation of mobile devices and/or for display to end users in a corresponding GUI (graphical user interface). In some cases, the MIGM system interacts with an MIGM system operator user, such as by displaying a GUI showing information related to the images and/or a floor plan being generated, and by receiving and using input submitted by the user via the GUI to assist with the generating of the floor plan, such as to specify interconnections between particular rooms via particular inter-room wall openings of the rooms.

Automated tools for generating building mapping information

Techniques are described for computing devices to perform automated operations to determine the acquisition locations of images, such as within a building interior based on automatically determined shapes of rooms of the building, and for using the determined image acquisition location information in further automated manners. The image may be a panorama image or of another type (e.g., a rectilinear perspective image) and acquired at an acquisition location in a multi-room building's interior, and the determined acquisition location for such an image may be at least a location on the building's floor plan and optionally an orientation/direction for at least a part of the image&#x2014;in addition, the automated image acquisition location determination may be further performed without having or using information from any depth sensors or other distance-measuring devices about distances from an image's acquisition location to walls or other objects in the surrounding building.

Automated determination of acquisition locations of acquired building images based on determined surrounding room data

Techniques are described for using computing devices to perform automated operations for determining the acquisition location of an image using an analysis of the image's visual contents. In at least some situations, images to be analyzed include panorama images acquired at acquisition locations in an interior of a multi-room building, and the determined acquisition location information includes a location on a floor plan of the building and in some cases orientation direction information&#x2014;in at least some such situations, the acquisition location determination is performed without having or using information from any distance-measuring devices about distances from an image's acquisition location to objects in the surrounding building. The acquisition location information may be used in various automated manners, including for controlling navigation of devices (e.g., autonomous vehicles), for display on one or more client devices in corresponding graphical user interfaces, etc.

Automated analysis of image contents to determine the acquisition location of the image

Techniques are described for automated operations to analyze visual data combined from multiple images captured in a room to determine the room shape, such as by iteratively refining alignment of the multiple images' visual data into a common coordinate system until alignment differences satisfy one or more defined criteria, and for subsequently using the determined room shape information in further automated manners. The images may be panorama images in an equirectangular or other spherical format, and determined room shapes for one or more rooms of a building may be fully closed three-dimensional shapes and used to improve navigation of the building (e.g., as part of a generated building floor plan)&#x2014;the automated room shape determination may be further performed without having or using information from any distance-measuring devices about distances from an image's acquisition location to walls or other objects in the surrounding room.

Automated room shape determination using visual data of multiple captured in-room images

Automated determination of image acquisition locations in building interiors using determined room shapes

Techniques are described for using computing devices to perform automated operations involved in analysis of images acquired in a defined area, as part of generating mapping information of the defined area for subsequent use (e.g., for controlling navigation of devices, for display on client devices in corresponding GUIs, etc.). The defined area may include an interior of a multi-room building, and the generated information including a floor map of the building, such as from an analysis of multiple 360&#xb0; spherical panorama images acquired at various viewing locations within the building (e.g., using an image acquisition device with a spherical camera having one or more fisheye lenses to capture a panorama image that extends 360 degrees around a vertical axis)&#x2014;the generating may be further performed without detailed information about distances from the images' viewing locations to objects in the surrounding building.

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Seattle, WA, United States of America

Yuguang Li