Abstract: Techniques are described for using computing devices to perform automated operations related to, with respect to a computer model of a house or other building's interior, generating and displaying simulated lighting information in the model based on sunlight or other external light that is estimated to enter the building and be visible in particular rooms of the interior under specified conditions, such as using ambient occlusion and light transport matrix calculations. The computer model may be a 3D (three-dimensional) or 2.5D representation that is generated after the house is built and that shows physical components of the actual house's interior (e.g., walls), and may be displayed to a user of a client computing device in a displayed GUI (graphical user interface) via which the user specifies conditions for which the simulated lighting display is generated.

Abstract: 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.

Abstract: A valuation system to identify interior features of a property, identify exterior features related to interior features using aerial images, and to generate property valuations based on the identified features is provided. The valuation system identifies, using a computer vision module, interior features based on interior image data (e.g., photos) of a property, and further identifies exterior features associated with any of the interior features based on an aerial photo of the property. For example, trees and buildings (e.g., exterior features) adjacent to a window (e.g., an interior feature) can be identified by a computer vision module through the combination of interior and exterior image data. In other words, the identification of property features by the computer vision module can be enriched by correlating interior image data (e.g., photos, video walkthroughs) to exterior image data (e.g., satellite photos, aerial photos).

Abstract: Techniques are described for using multiple devices to automatically determine the acquisition location of an image from a camera device, such as within a building interior and by using data from the multiple devices (e.g., visual data from the camera device's image, and additional data captured by a separate mobile computing device in the same area as the camera device), and for subsequently using determined image acquisition location information in one or more further automated manners. The image may be a panorama image or of another type, and the determined acquisition location for such an image may be at least a location on the building's floor plan—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.

Abstract: 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.

Abstract: 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—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.

Abstract: Techniques are described for using computing devices to perform automated operations for analyzing video (or other image sequences) 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 may include a floor map of the building, such as from an analysis of some or all image frames of the video (e.g., 360° image frames from 360° video) using structure-from-motion techniques to identify objects with associated plane and normal orthogonal information, and then clustering detected planes and/or normals from multiple analyzed images to determine likely wall locations. The generating may be further performed without using acquired depth information about distances from the video capture locations to objects in the surrounding building.

Abstract: Techniques are described for using multiple devices to automatically determine the acquisition location of an image from a camera device, such as within a building interior and by using data from the multiple devices (e.g., visual data from the camera device's image, and additional data captured by a separate mobile computing device in the same area as the camera device), and for subsequently using determined image acquisition location information in one or more further automated manners. The image may be a panorama image or of another type, and the determined acquisition location for such an image may be at least a location on the building's floor plan—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.

Abstract: 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.

Abstract: Techniques are described for using computing devices to perform automated operations for identifying building floor plans that have attributes satisfying target criteria and for subsequently using the identified floor plans in further automated manners. In at least some situations, the identification of such building floor plans is based on generating and using adjacency graphs generated for the floor plans that represent inter-connections between rooms and other attributes of the buildings, and in some cases is further based on generating and using embedding vectors that concisely represent the information of the adjacency graphs. Information about such identified building floor plans may be used in various automated manners, including for controlling navigation of devices (e.g., autonomous vehicles), for display on client devices in corresponding graphical user interfaces, for further analysis to identify shared and/or aggregate characteristics, etc.

Abstract: 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—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.

Abstract: Techniques are described for using multiple devices to automatically determine the acquisition location of an image from a camera device, such as within a building interior and by using data from the multiple devices (e.g., visual data from the camera device's image, and additional data captured by a separate mobile computing device in the same area as the camera device), and for subsequently using determined image acquisition location information in one or more further automated manners. The image may be a panorama image or of another type, and the determined acquisition location for such an image may be at least a location on the building's floor plan—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.

Abstract: 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.

Abstract: Techniques are described for using computing devices to perform automated operations for analyzing video (or other image sequences) 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 may include a floor map of the building, such as from an analysis of some or all image frames of the video (e.g., 360° image frames from 360° video) using structure-from-motion techniques to identify objects with associated plane and normal orthogonal information, and then clustering detected planes and/or normals from multiple analyzed images to determine likely wall locations. The generating may be further performed without using acquired depth information about distances from the video capture locations to objects in the surrounding building.

Abstract: Techniques are described for using computing devices to perform automated operations related to, with respect to a computer model of a house or other building's interior, generating and displaying simulated lighting information in the model based on sunlight or other external light that is estimated to enter the building and be visible in particular rooms of the interior under specified conditions, such as using ambient occlusion and light transport matrix calculations. The computer model may be a 3D (three-dimensional) or 2.5D representation that is generated after the house is built and that shows physical components of the actual house's interior (e.g., walls), and may be displayed to a user of a client computing device in a displayed GUI (graphical user interface) via which the user specifies conditions for which the simulated lighting display is generated.

Abstract: Techniques are described for using computing devices to perform automated operations for analyzing video (or other image sequences) 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 may include a floor map of the building, such as from an analysis of some or all image frames of the video (e.g., 360° image frames from 360° video) using structure-from-motion techniques to identify objects with associated plane and normal orthogonal information, and then clustering detected planes and/or normals from multiple analyzed images to determine likely wall locations. The generating may be further performed without using acquired depth information about distances from the video capture locations to objects in the surrounding building.

Abstract: Using computing devices to perform automated operations related to, with respect to a computer model of a house or other building's interior, generating and displaying simulated lighting information in the model based on sunlight or other external light that is estimated to enter the building and be visible in particular rooms of the interior under specified conditions, such as using ambient occlusion and light transport matrix calculations. The computer model may be a 3D (three-dimensional) or 2.5D representation that is generated after the house is built and that shows physical components of the actual house's interior (e.g., walls), and may be displayed to a user of a client computing device in a displayed GUI (graphical user interface) via which the user specifies conditions for which the simulated lighting display is generated.

Abstract: 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.

Abstract: Techniques are described for using computing devices to perform automated operations for analyzing video (or other image sequences) 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 may include a floor map of the building, such as from an analysis of some or all image frames of the video (e.g., 360° image frames from 360° video) using structure-from-motion techniques to identify objects with associated plane and normal orthogonal information, and then clustering detected planes and/or normals from multiple analyzed images to determine likely wall locations. The generating may be further performed without using acquired depth information about distances from the video capture locations to objects in the surrounding building.

Abstract: Techniques are described for using computing devices to perform automated operations related to, with respect to a computer model of a house or other building's interior, generating and displaying simulated lighting information in the model based on sunlight or other external light that is estimated to enter the building and be visible in particular rooms of the interior under specified conditions, such as using ambient occlusion and light transport matrix calculations. The computer model may be a 3D (three-dimensional) or 2.5D representation that is generated after the house is built and that shows physical components of the actual house's interior (e.g., walls), and may be displayed to a user of a client computing device in a displayed GUI (graphical user interface) via which the user specifies conditions for which the simulated lighting display is generated.