General Electric Company

Zillow, Inc.

Zillow Group, Inc.

Amazon Technologies, Inc.

Haier US Appliance Solutions, Inc.

Mftb Holdco, Inc.

Mfib Holdco, Inc.

Li Guan

Qi Shan

Alex Colburn

Ivaylo Boyadzhiev

Peter Henry Tu

Ser Nam Lim

Andrew H Otwell

Mitchell David Dawson

Dun-Yu Hsiao

Yi Yao

Ramin Mehran

Gang Hua

Dashan Gao

Jens Rittscher

Yuguang Li

Ting Yu

Kedar Anil Patwardhan

Ming-Ching Chang

Joseph Vincent Pawlowski

Shubao Liu

Xingwei Yang

Yogesh Agarwal

Srivatsa Dhanvantri

Binod Pandey

Dilip Kumar

Gerard Guy Medioni

David Scott Diwinsky

Jilin Tu

Charles Ray Smith

John Brandon Laflen

Yan Tong

Russell Robert Irving

Vinod Padmanabhan Kumar

Jose Abiel Garza

Craig Ronald Hoffmann

Peter Tu

Techniques are described for using computing devices to perform automated operations to control acquisition of images in a defined area, including obtaining and using data from one or more hardware sensors on a mobile device that is acquiring the images, analyzing the sensor data (e.g., in a real-time manner) to determine the geometric orientation of the mobile device in three-dimensional (3D) space, and using that determined orientation to control the acquisition of further images by the mobile device. In some situations, the determined orientation information may be used in part to automatically generate and display a corresponding GUI (graphical user interface) that is overlaid on and augments displayed images of the environment surrounding the mobile device during the image acquisition process, so as to control the mobile device's geometric orientation in 3D space.

Automated control of image acquisition via use of mobile device user interface

Techniques are described for automated operations involving capturing and analyzing information from an interior of a house, building or other structure, for use in generating and providing a representation of that interior. Such techniques may include using a user's mobile device to capture visual data from multiple viewing locations (e.g., video captured while the mobile device is rotated for some or all of a full 360 degree rotation at each viewing location) within multiple rooms, capturing data linking the multiple viewing locations, analyzing each viewing location's visual data to create a panorama image from that viewing location, analyzing the linking data to determine relative positions/directions between at least some viewing locations, creating inter-panorama links in the panoramas to each of one or more other panoramas based on such determined positions/directions, and providing information to display multiple linked panorama images to represent the interior.

Capture, analysis and use of building data from mobile devices

Automated control of image acquisition via use of mobile device interface

An optical imaging and processing system includes an optical element and a processor configured to process the plurality of image frames to generate a three-dimensional model of at least a portion of the turbine component interior. The system may also include a display coupled to the processor to display the three-dimensional model. An operator may view and analyze the three-dimensional model on the display for defects. The processor may further be configured to automatically navigate the three-dimensional model to determine defects within the turbine component interior. The system may also include a repositioning device configured to reposition the optical element such that the optical element may capture the plurality of image frames from multiple vantage points within the turbine component interior.

System and method for engine inspection

Techniques are described for using computing devices to perform automated operations to generate mapping information using inter-connected images of a defined area, and for using the generated mapping information in further automated manners. In at least some situations, the defined area includes an interior of a multi-room building, and the generated information includes a floor map of the building, such as from an automated analysis of multiple panorama images or other images acquired at various viewing locations within the building&#x2014;in at least some such situations, the generating is further performed without having detailed information about distances from the images' viewing locations to walls or other objects in the surrounding building. The generated floor map and other mapping-related information may be used in various 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.

Use of automated mapping information from inter-connected images

Automated mapping information generation from inter-connected images

Automated control of image acquisition via use of hardware sensors and camera content

Automated control of image acquisition via acquisition location determination

Techniques are described for, given two images taken at two viewing locations, generating and presenting an image transition sequence that simulates viewer movement between the viewing locations, such as without using information about relative distance between the viewing locations and other depth information to objects in an environment around the viewing locations. The start and end images for an image transition sequence may be part of panorama images acquired at the viewing locations, and generating of the image transition sequence may include selecting and using one of multiple types of transition sequences to perform rotating (e.g., from a start image's viewing direction to face toward the viewing location for the end image), zooming (e.g., to simulate moving forward), and/or blending of the end image with a modified version of the start image, with the resulting image transition sequence played as a video or other animation.

Presenting image transition sequences between viewing locations

Techniques are described for automated operations involving acquiring and analyzing information from an interior of a house, building or other structure, for use in generating and providing a representation of that interior. Such techniques may include using a user's mobile device to capture video data from multiple viewing locations (e.g., 360&#xb0; video at each viewing location) within multiple rooms, and capturing data linking the multiple viewing locations (e.g., by recording video, acceleration and/or other data from the mobile device as the user moves between the two viewing locations), creating a panorama image for each viewing location, analyzing the linking information to model the user's travel path and determine relative positions/directions between at least some viewing locations, creating inter-panorama links in the panoramas to each of one or more other panoramas based on such determined positions/directions, and providing information to display multiple linked panorama images to represent the interior.

Connecting and using building data acquired from mobile devices

An optical imaging and processing system includes an optical connection and an optical element disposed at a first end of the optical connection. The first end of the optical connection is configured to extend into a turbine component interior such that the optical element is disposed within the turbine component interior. The system also includes a photodiode array disposed at a second end of the optical connection, where the optical element is configured to transmit a video stream of the turbine component interior to the photodiode array as the optical element is moved within the turbine component interior between multiple vantage points. The system also includes a processor coupled to the photodiode array, wherein the processor is configured to process the video stream to generate a three-dimensional model of at least a portion of the turbine component interior without utilizing a previously defined three-dimensional model input of the turbine component interior.

The presence of an object in a query image may be searched for using a feature of the query image. A local descriptor value for the feature is first determined. Previously stored object data for various 3D objects is then retrieved, with each set of stored object data including a probability distribution that describes a feature of a 3D object as obtained from images at different camera poses. A probability value is then determined using the local descriptor value for the feature in the query image and the available distribution data from the stored object data. The distribution data is then ranked based on the resulting probability values and the highest ranked distribution data is associated with the feature in the query image. Output data may also be generated to identify the 3D object in the query image based on an object identifier of the highest ranked distribution data.

System to search three-dimensional object data

Growing community of inventors

Bellevue, WA, United States of America

Li Guan