Microsoft Technology Licensing, LLC

Amazon Technologies, Inc.

Microsoft Corporation

Yasser Baseer Asmi

Sudarshan Narasimha Raghavan

Ohil Krishnamurthy Manyam

Gopi Prashanth Gopal

Daniel Bibireata

Xiaofeng Ren

Ammar Chinoy

James David Macauley

Avishkar Misra

Ling Tony Chen

Nishitkumar Ashokkumar Desai

Michal Bortnik

Steven Dale Lamb

Erik John Arthur

Christopher Robert Towers

James Nicholas Helm

Abhishek Abhishek

Emilio Ian Maldonado

Zhengyou Zhang

Khawar Zuberi

Liefeng Bo

Frank Florian Liberato, Jr

Rouzbeh Aminpour

Jie Jerry Liu

Di Wang

Ramanathan Palaniappan

Megan Lesley Tedesco

Muralidhar Koka

Hao Jiang

Yi Lu

Dimitrios Lymberopoulos

Jon Marcus Randall Whitten

Michel Goraczko

Ali Dalloul

Tony Capone

Ivan J Leichtling

Alice Pritikin Steinglass

Long Xuan Nguyen

Christopher Michael Pirich

Jaechul Kim

David Walter Proctor

Nadya Dhalla

Jeffrey Edward Simon

Sudheer Babu Ramoji

Dilip Kumar

Hui Shen

Korwin Jon Smith

Jiandong Ruan

Michel Leonard Goldstein

Navid Shiee

Andrew Murphy

Brian Lloyd Schmidt

Thamer A Abanami

Prafulla Jinendra Masalkar

Jonathan E Lange

Mohsen M Agsen

Gregory A Martinez

Chunshui Zhao

Ismael Medrano

Jeffrey David Henshaw

David Allen Smith

Nicolas Guillaume Hostein

Tracy Sharpe

Richard Henry Irving

Shrivatsan Vasudhevan

Joachim Sebastian Stahl

Smita Joshi

Pranab Mohanty

Scott Robert Marison

Craig Lichtenstein

Mark D Zuber

Roxana Arama

William Thomas

Michael Cory Maston

Jonathan G Thomason

Robert Whittemore Dreyfoos

Todd Nelson Schoepflin

Tyler Scott Carper

Bradley David Volen

Jonathan Gerald Thomason

Tracy Clayton Sharpe

Described is a system for counting stacked items using image analysis. In one implementation, an image of an inventory location with stacked items is obtained and processed to determine the number of items stacked at the inventory location. In some instances, the item closest to the camera that obtains the image may be the only item viewable in the image. Using image analysis, such as depth mapping or Histogram of Oriented Gradients (HOG) algorithms, the distance of the item from the camera and the shelf of the inventory location can be determined. Using this information, and known dimension information for the item, a count of the number of items stacked at an inventory location may be determined.

Determining inventory changes at an inventory location

Described is a multiple-camera system and process for determining an item involved in an event. For example, when a user picks an item or places an item at an inventory location, image information for the item may be obtained and processed to identify the item involved in the event and associate that item with the user.

Store tracking system

The discussion relates to inventory control. In one example, a set of ID sensors can be employed in an inventory control environment and subsets of the ID sensors can collectively sense tagged items in shared space. Data from the subset of ID sensors can indicate when a user has taken possession of an individual tagged item in the shared space.

Inventory control

This disclosure describes an item drop location for placing items that have been picked from an inventory location within a material handling facility but have not yet been transitioned from the materials handling facility and a return location for returning items that have been transitioned from the materials handling facility. Likewise, described is a system and method for identifying an item placed at a drop location or an item placed at a return location, processing the placed item and providing confirmation to a user that placed the item and facilitating a return of the item or a removal of the item from an item identifier list associated with the user.

Inventory item release apparatus and method

Described are systems and techniques configured to authenticate a user upon entry to a facility. Prior to entry, the user may log in to a secure website with valid credentials, whereupon a login image of the user at the time of login is acquired. In one implementation, optically encoded data is generated which includes data representative of the login image, an acquisition timestamp, and an identifier value. At entry of the user to the facility, an entry image of the user's face, an image of the optically encoded data as presented on a display of a computing device in possession of the user, and an entry timestamp are acquired. By determining the timestamp is within a valid range of time and the data representative of the login image corresponds to the entry image, the user is authenticated to the identifier value.

User authentication system

Determining an item involved in an event at an event location

Sensors in a facility generate sensor data associated with a region of the facility, which can be used to determine a 3D location of an object in the facility. Some sensors may sense overlapping regions of the facility. For example, a first sensor may generate data associated with a first region of the facility, while a second sensor may generate data associated with a second region of the facility that partially overlaps the first region. Sensors may fail at times as determined from sensor output data or status data. In response to identifying a failed sensor, an undetected region corresponding to the failed sensor is identified, as well as a substitute sensor that partially senses the undetected region. Sensor data from the substitute sensor, such as 2D data, is acquired and used to estimate a 3D location of an object in the undetected region.

Management of sensor failure in a facility

Point-of-sale systems may include stations having interactive monitors mounted at specific heights and angles that permit such monitors to be viewed and interacted with by an associate or a customer. Some point-of-sale systems may include two stations, each having a monitor aligned in opposite directions, a user of one monitor may not view the other monitor, and vice versa. The point-of-sale systems may also include instrument readers (e.g., credit card readers or NFC readers) for recognizing payment instruments of customers and identifying the customers based on the payment instruments. Each of the monitors and instrument readers may be linked by cables to computer devices that are securely housed in a chamber above which the monitors are mounted. The monitors and other components are installed in a modular fashion, and may be independently installed or replaced without requiring an installation or replacement of the entire point-of-sale system.

Secure dual-monitor point-of-sale system

The discussion relates to context-aware environments. One example can include inwardly-facing cameras positioned around a periphery of an environment that defines a volume. The example can also include sensors positioned relative to the volume and configured to communicate with a user device in the volume. The example can also include an ambient perception component configured to track user locations in the volume and to detect user gestures relative to objects in the volume, and responsive to receiving a query from the user's device, to supplement the query with information derived from the objects.

Context-awareness

This disclosure describes a system for assisting users in locating items from inventory locations and/or obtaining additional information about items. In some instances, a user may experience difficulty in locating an inventory item in a materials handling facility. By detecting one or more expressions presented by the user, an inventory management system may determine that assistance is to be provided to the user, determine and provide the appropriate assistance to the user.

Expression and gesture based assistance

Described is a multiple-camera system and process for detecting a user within a materials handling facility and tracking a position of the user as the user moves through the materials handling facility. In one implementation, a plurality of depth sensing cameras are positioned above a surface of the materials handling facility and oriented to obtain a top-down view of the surface of the materials handling facility, along with any objects (e.g., users) on the surface of the materials handling facility. The depth information from the cameras may be utilized to detect objects on the surface of the materials handling facility, track a movement of those objects and determine if those objects are users.

Collecting user pattern descriptors for use in tracking a movement of a user within a materials handling facility

Systems and method for providing a single sign in a gaming console that associates online activity that is out-of-game/cross game, and/or online activity that is in-game, and/or activity that is offline and in-game with that account. While online, a service tracks activity of gamers and provides usage statistics in a profile. While offline, the game console tracks the player's activity via a mechanism to collect detailed information about a specific player's in-game statistics and accomplishments. The offline activity is cached and uploaded when the console connects to the online service. Players can accumulate achievements offline that are credited towards online activities.

Application interface for tracking player identity

An item stowed at an inventory location may rest or be supported by a surface, such as a shelf, that includes an optical sensor array. The optical sensor array comprises a plurality of optical sensors that detect light intensity values. When a light source illuminates the item resting on the surface, a footprint or shadow is cast by the item onto the surface. Such a shadow is detected by the light intensity values at the optical sensors in the optical sensor array. Once the shadow is detected, information about the area, shape, and perimeter of the shadow can be determined and saved as footprint data for a single item. Such a process can be performed at intake of the item to the facility and later accessed to determine a quantity of the item on a shelf of a facility.

Generation of footprint data for items

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Redmond, WA, United States of America

Yasser Baseer Asmi