Microsoft Technology Licensing, LLC

Christopher Stephen Messer

Michael Bleyer

Raymond Kirk Price

Naveen Thumpudi

Blaise Aguera Y Arcas

Wei-Ge Chen

Denis Demandolx

Yuri Pekelny

Sudipta Narayan Sinha

Serge Smirnov

David J Simons

Eric Joel Stollnitz

Timothy E Onders

Raymond Cheng

James Evan Undery

Michael John Schoenberg

Maksim Lepikhin

Timo Pekka Pylvaenaeinen

Philip Starhill

Donald A Barnett

Keith Seifert

Johannes Peter Kopf

Markus Unger

Disclosed embodiments include methods and systems for utilizing a structured projection pattern to perform depth detection. In some instances, the structured projection pattern forms a dot pattern, which is projected by a projector, wherein the projector includes one or more infrared (IR) light dot pattern illuminators for projecting an IR light dot pattern to a surrounding environment. The IR dot pattern light that is at least partially reflected off one or more objects in the surrounding environment is detected by one or more cameras attached to a head-mounted display (HMD). The HMD, which is physically untethered from the projector, utilizes the captured IR dot pattern light reflections to track movement of the HMD and/or perform depth detection of one or more objects in the environment surrounding the HMD.

External IR illuminator enabling improved head tracking and surface reconstruction for virtual reality

A first image and a second image of a scene are obtained for use in detecting the location of the floor in the scene. A first of the images is mapped onto a candidate plane that is perpendicular to a gravity vector, thereby creating a texture-mapped plane. The texture-mapped plane is projected into the geometry of the camera utilized to take the second image to create an artificial first image. A comparison is then performed between the first image and the artificial first image to generate a similarity score. Multiple candidate planes are processed in this manner for the first and second images, and the candidate plane generating the highest associated similarity score is chosen as the floor. This process can be repeated for multiple sets of stereo images.

Floor detection in virtual and augmented reality devices using stereo images

Ambiguous portions of an image which have fewer photons of a reflected light signal detected than required to determine depth can be classified as being dark (i.e., reflecting too few photons to derive depth) and/or far (i.e., beyond a range of a camera) based at least in part on expected depth and reflectivity values. Expected depth and reflectivity values for the ambiguous portions of the image may be determined by analyzing a model of an environment created by previously obtained images and depth and reflectivity values. The expected depth and reflectivity values may be compared to calibrated values for a depth sensing system to classify the ambiguous portions of the image as either dark or far based on the actual photon count detected for the image.

Model-based classification of ambiguous depth image data

An input mesh can be decomposed into component meshes that can be independently simplified. A computing device can calculate costs of performing candidate edge collapses for a component mesh. The candidate edge collapses can include boundary edge collapses and interior edge collapses. To simplify a component mesh, the execution of boundary edge collapses and the execution of interior edge collapses are interleaved in an order based on the costs of performing the candidate edge collapses. The position of a vertex resulting from a boundary edge collapse can be calculated independently of the interior of the component mesh. When component meshes are simplified in parallel, a boundary that is common to the component meshes can be simplified identically.

Maintaining consistent boundaries in parallel mesh simplification

A compressed digital audio signal is transmitted from an audio source along a connection wire to an audio receiver. The digital audio signal can encode digital audio data having different sampling frequencies, frames sizes, and other information. The audio receiver that receives the digital audio signal can decode and convert the compressed digital audio signal into multiple synchronized analog signals, which are used to drive multiple speakers. The audio receiver may also synchronize the audio data with associated video data so that the audio playback and video playback are 'in sync', despite delay introduced by the audio signal decoding at the audio receiver.

Digital audio processing

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Christopher Stephen Messer