Microsoft Technology Licensing, LLC

Joseph Milan Filcik

Ryan S Menezes

Hongli Deng

Gabriel Blanco Saldana

Steven Miles Greenberg

Shen Wang

Brian Eugene Kihneman

Vijayalakshmi Ramkumar

Chris Seitzinger

Hao Yan

Tony Ducheng Jin

Jonathan McPherson

David Michael Jade

Juventino Rojas Arredondo

Cameron Elliot Smith

Chenyang Li

A method to predict a traversal-time interval for traversal of a service queue comprises receiving video of a region including the service queue, recognizing in the video, via machine vision, a plurality of persons awaiting service within the region, estimating an average crossing-time interval between successive crossings, by the plurality of persons, of a fixed boundary along the service queue, wherein such estimating is based on features of the service queue and of the one or more persons awaiting service, and returning an estimate of the traversal-time interval based on a count of the persons awaiting service and on the average crossing-time interval as estimated.

Machine-vision person tracking in service environment

Techniques for inferring whether an event is occurring in 3D space based on 2D image data and for maintaining a camera's calibration are disclosed. An image of an environment is accessed. Input is received, where the input includes a 2D rule imposed against a ground plane. The 2D rule includes conditions indicative of an event. A bounding box is generated and encompasses a detected object. A point within the bounding box is projected from a 2D-space image plane of the image into 3D space to generate a 3D-space point. Based on the 3D-space point, a 3D-space ground contact point is generated. That 3D-space ground contact point is reprojected onto the ground plane of the image to generate a synthesized 2D ground contact point. A location of the synthesized 2D ground contact point is determined to satisfy the conditions.

Accurate video event inference using 3D information

Technologies are described herein for filtering data in a result set using inexact and/or culture dependent terms. A user provides one or more filter terms for filtering a result set being viewed. One or more data type interpretations are determined for each filter term based on the value of the term. The data type interpretations may further be based on a locale associated with the user. For each filter term, the columns of the result set to which the filter term is to be applied is selected based on the data type interpretations determined for the filter term and the data types of the columns. The filter terms are then applied to the selected columns of the result set, thus causing the rows of the result set as displayed to the user to be limited to rows wherein at least one column value satisfies a filter term.

Filtering structured data using inexact, culture-dependent terms

Technologies are described herein for providing a two-tier failover service. A request to access content by an application associated with an application identifier may be identified. A first record corresponding to the application identifier may be retrieved from a database information table. The first record may include a reference identifier, a database name of a database, and a failover value. A second record corresponding to the reference identifier may be retrieved from a server information table. The second record may include an indication of a first server computer as a primary server computer and an indication of a second server computer as a secondary server computer. A connection specification to either the first server computer or the second server computer may be generated based on the first record and the second record.

Two-tier failover service for data disaster recovery

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Bellevue, WA, United States of America

Joseph Milan Filcik