The present disclosure relates to methods and devices for performing depth estimation on image data. In one example, a device performs depth estimation on first and second images captured using one or more cameras having a color filter array. Each, image of the first and second images comprises multiple color channels. Each color channel of the multiple color channels corresponds to a respective color channel of the color filter array.sub.. The, device performs the depth estimation by estimating disparity from the color channels of the first and second images.

Systems, devices, and methods disclosed herein may generate captured views and a plurality of intermediate views within a pixel disparity range, T.sub.d, the plurality of intermediate views being extrapolated from the captured views.

Systems, devices, and methods disclosed herein may generate captured views and a plurality of intermediate views within a pixel disparity range, T.sub.d, the plurality of intermediate views being extrapolated from the captured views.

Systems and methods herein describe using a neural network to identify a first set of joint location coordinates and a second set of joint location coordinates and identifying a three-dimensional hand pose based on both the first and second sets of joint location coordinates.

Systems and methods herein describe using a neural network to identify a first set of joint location coordinates and a second set of joint location coordinates and identifying a three-dimensional hand pose based on both the first and second sets of joint location coordinates.

A captured scene captured of a live action scene while a display wall is positioned to be part of the live action scene may be processed. To perform the processing, image data of the live action scene having a live actor and the display wall displaying a first rendering of a precursor image is received. Further, precursor metadata for the precursor image displayed on the display wall and display wall metadata for the display wall is determined. An image matte is accessed, where the image matte indicates a first portion associated with the live actor and a second portion associated with the precursor image on the display wall in the live action scene. Pixel display values to add or modify an image effect or a visual effect are determined, and the image data is adjusted using the pixel display values and the image matte.

A structural analysis computing device may generate a proposed insurance claim and/or generate a proposed insurance quote for an object pictured in a three-dimensional (3D) image. The structural analysis computing device may be coupled to a drone configured to capture exterior images of the object. The structural analysis computing device may include a memory, a user interface, an object sensor configured to capture the 3D image, and a processor in communication with the memory and the object sensor. The processor may access the 3D image including the object, and analyze the 3D images to identify features of the object—such as by inputting the 3D image into a trained machine learning or pattern recognition program. The processor may generate a proposed claim form for a damaged object and/or a proposed quote for an uninsured object, and display the form to a user for their review and/or approval.

An HMD device is configured to vertically adjust the ground plane of a rendered virtual reality environment that has varying elevations to match the flat real world floor so that the device user can move around to navigate and explore the environment and always be properly located on the virtual ground and not be above it or underneath it. Rather than continuously adjust the virtual reality ground plane, which can introduce cognitive dissonance discomfort to the user, when the user is not engaged in some form of locomotion (e.g., walking), the HMD device establishes a threshold radius around the user within which virtual ground plane adjustment is not performed. The user can make movements within the threshold radius without the HMD device shifting the virtual terrain. When the user moves past the threshold radius, the device will perform an adjustment as needed to match the ground plane of the virtual reality environment to the real world floor.

Embodiments include a method for self-rectification of a stereo camera, wherein the stereo camera comprises a first camera and a second camera, the method comprises creating image pairs from a first images taken by the first camera and second images taken by the second camera, respectively, such that each image pair comprises two images taken at essentially the same time by the first camera and the second camera, respectively. The method comprises creating, for each image pair, matching point pairs from corresponding points in the two images of each image pair, such that each matching point pair comprises one point from each of the first and second image of the respective image pair. For each matching point pair, a disparity is calculated and a plurality of disparities is created for each image pair, and the resulting plurality of disparities is taken into account for the self-rectification.

Certain aspects of the technology disclosed herein integrate a camera with an electronic display. An electronic display can include several layers, such as a cover layer, a color filter layer, a display layer including light emitting diodes or organic light emitting diodes, a thin film transistor layer, etc. A processor initiates light emission from a plurality of display elements. The processor can suspend the light emission from the plurality of display elements for a period of time imperceptible to a human observer. The processor initiates a camera to capture an image during the period of time the plurality of display elements are suspended. The processor can capture a plurality of images corresponding to a plurality of pixels and produce an image comprising depth information.