Microsoft Technology Licensing, LLC

Bhaven P Dedhia

Tommer Leyvand

Jinyu Li

Craig C Peeper

Robert Matthew Craig

Casey Leon Meekhof

Ketan K Dalal

Vladimir Tankovich

Tim Keosababian

Ronald Forbes

Timothy Gerken

Geoffrey John Hulten

Yaron Eshet

A candidate human head is found in depth video using a head detector. A head region of light intensity video is spatially resolved with a three-dimensional location of the candidate human head in the depth video. Facial recognition is performed on the head region of the light intensity video using a face recognizer.

Identification using depth-based head-detection data

The description relates to estimating object orientation. One example includes determining a first estimate of object orientation using a first technique and image data. In this example, a second estimate of the object orientation can be determined using a second technique and the image data. The first estimate can be corrected with the second estimate to generate a corrected object orientation estimate which can be output.

Object orientation estimation

A computing system such as a game console maintains and updates a biometric profile of a user. In one aspect, biometric data of the user is continuously obtained from a sensor such as an infrared and visible light camera, and used to update the biometric profile using a machine learning process. In another aspect, a user is prompted to confirm his or her identify when multiple users are detected at the same time and/or when the user is detected with a confidence level which is below a threshold. A real-time image of the user being identified can be displayed on a user interface with user images associated with one or more accounts. In another aspect, the biometric profile is managed by a shell on the computing system, where the shell makes the biometric profile available to any of a number of applications on the computing system.

Managed biometric identity

Classifying pixels in a digital image includes receiving a primary image from a primary image sensor. The primary image includes a plurality of primary pixels. Depth information from a depth sensor is also received. The depth information and the primary image are cooperatively used to identify whether a primary pixel images a foreground subject or a background subject.

Foreground subject detection

Classifying pixels in a digital image includes receiving a primary image from one or more image sensors. The primary image includes a plurality of primary pixels. A depth image from one or more depth sensors is also received. The depth image includes a plurality of depth pixels, each depth pixel registered to one or more primary pixels. The depth image and the primary image are cooperatively used to identify whether a primary pixel images a foreground subject or a background subject.

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Redmond, WA, United States of America

Bhaven P Dedhia