Abstract: Techniques are described for using computing devices to perform automated operations for using generated building information to further generate and present visual data enhancements on images that are captured by and displayed on a mobile device in the building (e.g., concurrent with capture of the images by a camera of the mobile device, such as in a real-time or near-real-time manner with respect to image capture), such as using descriptive information about a building that is generated from analysis of acquired building images and optionally other building information (e.g., floor plans), and such as to improve navigation of the building (e.g., for autonomous vehicles) and provide other functionality as the mobile device moves through the building. The descriptive building information may include structural elements and other objects identified in the building and other determined attributes of the building, and automatically generated textual descriptions of the objects and other attributes.

Abstract: Techniques are described for using computing devices to perform automated operations for automatically generating information about attributes of buildings from automated analysis of building information that includes floor plans and acquired building images and to subsequently using the generated building information in one or more further automated manners. In some situations, such automated generation of building information includes automatically determining objects in a building and other attributes of the building, and automatically generating descriptions about the determined building attributes. Information about such determined attributes and generated descriptions may be used in various automated manners, including for updating and/or validating information in existing building descriptions, for determining matching buildings that have similarities to indicated building descriptions or other specified criteria, for controlling device navigation (e.g.

Abstract: Techniques are described for automated operations related to analyzing visual data from images captured in rooms of a building and optionally additional captured data about the rooms to assess room layout and other usability information for the building's rooms and optionally for the overall building, and to subsequently using the assessed usability information in one or more further automated manners, such as to improve navigation of the building. The automated operations may include identifying one or more objects in each of the rooms to assess, evaluating one or more target attributes of each object, assessing usability of each object using its target attributes' evaluations and each room using its objects' assessment and other room information with respect to an indicated purpose, and combining the assessments of multiple rooms in a building and other building information to assess usability of the building with respect to its indicated purpose.

Abstract: Techniques are described for using computing devices to perform automated operations to generate mapping information of a defined area via analysis of visual data of images, including by using attribute information exchanged between paired or otherwise grouped images of multiple types to generate enhanced images, and for using the generated mapping information in further automated manners, including to use the generated mapping information for automated navigation and/or to display or otherwise present the generated mapping information. In some situations, the defined area includes an interior of a multi-room building, and the generated information includes at least one or more enhanced images and/or a partial floor plan and/or other modeled representation of the building, with the generating performed in some cases without having measured depth information about distances from the images' acquisition locations to walls or other objects in the surrounding building.

Abstract: Techniques are described for using computing devices to perform automated operations for determining matching buildings and using corresponding information in further automated manners, such as by determining buildings having similarities to other indicated buildings based at least in part on building floor plans and/or other attributes, and by automatically generating descriptions of the similarities. In some situations, such matching building determinations are based on generating and using adjacency graphs for floor plans that represent inter-connections between rooms and other attributes of the buildings, and further generating and comparing vector-based embeddings that concisely represent the information of the adjacency graphs for use in performing inter-building comparisons and generating the descriptions. Information about such determined buildings may be used in various automated manners, including for controlling device navigation (e.g.

Abstract: Aspects of the subject disclosure are directed towards safely projecting a diffracted light pattern, such as in an infrared laser-based projection/illumination system. Non-diffracted (zero-order) light is refracted once to diffuse (defocus) the non-diffracted light to an eye safe level. Diffracted (non-zero-order) light is aberrated twice, e.g., once as part of diffraction by a diffracting optical element encoded with a Fresnel lens (which does not aberrate the non-diffracted light), and another time to cancel out the other aberration; the two aberrations may occur in either order. Various alternatives include upstream and downstream positioning of the diffracting optical element relative to a refractive optical element, and/or refraction via positive and negative lenses.

Abstract: Techniques are described for automated operations related to analyzing visual data from images captured in rooms of a building and optionally additional captured data about the rooms to assess room layout and other usability information for the building's rooms and optionally for the overall building, and to subsequently using the assessed usability information in one or more further automated manners, such as to improve navigation of the building. The automated operations may include identifying one or more objects in each of the rooms to assess, evaluating one or more target attributes of each object, assessing usability of each object using its target attributes' evaluations and each room using its objects' assessment and other room information with respect to an indicated purpose, and combining the assessments of multiple rooms in a building and other building information to assess usability of the building with respect to its indicated purpose.

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 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 to generate mapping information of a defined area via analysis of visual data of images, including by using attribute information exchanged between paired or otherwise grouped images of multiple types to generate enhanced images, and for using the generated mapping information in further automated manners, including to use the generated mapping information for automated navigation and/or to display or otherwise present the generated mapping information. In some situations, the defined area includes an interior of a multi-room building, and the generated information includes at least one or more enhanced images and/or a partial floor plan and/or other modeled representation of the building, with the generating performed in some cases without having measured depth information about distances from the images acquisition locations to walls or other objects in the surrounding building.

Abstract: Techniques are described for automated operations related to analyzing visual data from images captured in rooms of a building and optionally additional captured data about the rooms to assess room layout and other usability information for the building's rooms and optionally for the overall building, and to subsequently using the assessed usability information in one or more further automated manners, such as to improve navigation of the building. The automated operations may include identifying one or more objects in each of the rooms to assess, evaluating one or more target attributes of each object, assessing usability of each object using its target attributes' evaluations and each room using its objects' assessment and other room information with respect to an indicated purpose, and combining the assessments of multiple rooms in a building and other building information to assess usability of the building with respect to its indicated purpose.

Abstract: Techniques are described for using a smart phone or other mobile device to perform automated operations for generating panorama images of building environments and for subsequently using the generated panorama images in further automated manners. In at least some situations, the generation of a panorama image by a mobile device is based at least in part on automatically acquiring multiple constituent images on the mobile device in multiple directions from an acquisition location and on concurrently combining acquired constituent images on the mobile device, such as in a real-time manner relative to the constituent image capture, to generate a panorama image with 360° of horizontal coverage of the view from that acquisition location. 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, 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 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: The subject disclosure is directed towards controlling the intensity of illumination of a scene or part of a scene, including to conserve illumination power. Quality of depth data in stereo images may be measured with different illumination states; environmental conditions, such as ambient light, natural texture may affect the quality. The illumination intensity may be controllably varied to obtain sufficient quality while conserving power. The control may be directed to one or more regions of interest corresponding to an entire scene or part of a scene.

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 a smart phone or other mobile device to perform automated operations for generating panorama images of building environments and for subsequently using the generated panorama images in further automated manners. In at least some situations, the generation of a panorama image by a mobile device is based at least in part on automatically acquiring multiple constituent images on the mobile device in multiple directions from an acquisition location and on concurrently combining acquired constituent images on the mobile device, such as in a real-time manner relative to the constituent image capture, to generate a panorama image with 360° of horizontal coverage of the view from that acquisition location. 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, etc.

Abstract: An “Adaptive Exposure Corrector” performs automated real-time exposure correction of individual images or image sequences of arbitrary length. “Exposure correction” is defined herein as automated adjustments or corrections to any combination of shadows, highlights, high-frequency features, and color saturation of images. The Adaptive Exposure Corrector outputs perceptually improved images based on image ISO and camera ISO capabilities in combination with camera noise characteristics via exposure corrections by a variety of noise-aware image processing functions. An initial calibration process adapts these noise aware image processing functions to noise characteristics of particular camera models and types in combination with particular camera ISO settings. More specifically, this calibration process precomputes a Noise Aware Scaling Function (NASF) and a Color Scalar Function (CSF).

Abstract: An “Adaptive Exposure Corrector” performs automated real-time exposure correction of individual images or image sequences of arbitrary length. “Exposure correction” is defined herein as automated adjustments or corrections to any combination of shadows, highlights, high-frequency features, and color saturation of images. The Adaptive Exposure Corrector outputs perceptually improved images based on image ISO and camera ISO capabilities in combination with camera noise characteristics via exposure corrections by a variety of noise-aware image processing functions. An initial calibration process adapts these noise aware image processing functions to noise characteristics of particular camera models and types in combination with particular camera ISO settings. More specifically, this calibration process precomputes a Noise Aware Scaling Function (NASF) and a Color Scalar Function (CSF).