Microsoft Technology Licensing, LLC

William Thomas

Zhengyou Zhang

Jie Jerry Liu

Jinyu Li

Yasser Baseer Asmi

Ankur Patel

Di Wang

Brandon Brian Murdoch

Ariel Nicolas Gordon

Khawar Zuberi

Sarat Chandra Subramaniam

Chunshui Zhao

Pieter Kasselman

Sam Franklin Williams, Iii

Yang Chen

Eric Wayne Doerr

Michael Robert Van Waardhuizen

Steven Bowles

Qingfen Lin

Jonathan Yoder Brenner

Tia Bianca Caldwell

Amy Caryl Nathanson

Preeti Rastogi

Youyou Han Oppenlander

Technology that permits two computing systems to communicate with each other with high confidence that a particular entity is present at the other computing system. As an example, when a first computing system communicates with a second computing system, the first computing system may regularly verify that a particular entity is present at the second computing system. The first computing system is actually in control of a proof capture component on the second computing system. The first computing system causes the second computing system to automatically generate proof of presence, the proof evidencing that the particular entity is present at the second computing system. The first computing system also causes the second computing system to include the generated presence proof when communicating from the second computing system to the first computing system.

Network communication using proof of presence

The disclosure herein describes systems and methods for object data storage. In some examples, the method includes generating a profile for an object in a directory, the profile including a first feature vector corresponding to the object and a global unique identifier (GUID) corresponding to the first feature vector in the profile; generating a search scope, the search scope including at least the GUID corresponding to the profile; generating a second feature vector from a live image scan; matching the generated second feature vector from the live image scan to the first feature vector using the generated search scope; identifying the GUID corresponding to the first feature vector that matches the second feature vector; and outputting information corresponding to the object of the profile identified by the GUID corresponding to the first feature vector.

Biometric data storage using feature vectors and associated global unique identifier

The disclosure relates to tracking the location of a target object. In one example, a computer vision system detects a configuration of environment objects. A location model that has been trained for the environment configuration is selected. A signal associated with the target object is received and interpreted using the selected location model to determine the location of the target object.

Location tracking

Systems, methods, and computer-readable storage media are provided for discovering and disambiguating identity providers such that user knowledge of appropriate identity providers is minimized. Users are presented with options for selecting appropriate providers only when multiple providers have user profiles matching a user identifier. When users are presented with options for selecting appropriate providers, providers that have user profiles matching the identifier are identified utilizing identity information for the application that utilizes the identity provider for its users rather than information identifying the identity provider itself. Where it is determined that no identity provider has a user profile associated with the user identifier (or where it is determined that a particular identity provider would generally be appropriate to be utilized with the user identifier), the opportunity for users to create an authentication account with one or more identity providers or to retry with a different user identifier is provided.

Discovering and disambiguating identity providers

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Redmond, WA, United States of America

William Thomas