Amazon Technologies, Inc.

Kartik Muktinutalapati

Nishitkumar Ashokkumar Desai

Gerard Guy Medioni

Dilip Kumar

Jayakrishnan Kumar Eledath

Daniel Bibireata

Kushagra Srivastava

Jaechul Kim

Hoi Cheung Pang

Shaonan Zhang

Waqas Syed Ahmed

Danny Guan

Jean Laurent Guigues

Pahal Kamlesh Dalal

Jiajun Zhao

Robert Matthias Steele

Alessandro Bergamo

Joseph M Alyea

Longlong Zhu

Marian Nasr Amin George

Lu Xia

Ivan Stankovic

This disclosure is directed to techniques in which a first user in an environment scans visual indicia associated with an item, such as a barcode, before handing the item to a second user. One or more computing devices may receive an indication of the scan, retrieve image data of the interaction from a camera within the environment, identify the user that received the item, and update a virtual cart associated with the second user to indicate addition of the item.

Analyzing sensor data to identify events

Where an event is determined to have occurred at a location within a vicinity of a plurality of actors, imaging data captured using cameras having the location is processed using one or more machine learning systems or techniques operating on the cameras to determine which of the actors is most likely associated with the event. For each relevant pixel of each image captured by a camera, the camera returns a set of vectors extending to pixels of body parts of actors who are most likely to have been involved with an event occurring at the relevant pixel, along with a measure of confidence in the respective vectors. A server receives the vectors from the cameras, determines which of the images depicted the event in a favorable view, based at least in part on the quality of such images, and selects one of the actors as associated with the event accordingly.

Associating events with actors using digital imagery and machine learning

In a materials handling facility, events may be associated with users based on imaging data captured from multiple fields of view. When an event is detected at a location within the fields of view of multiple cameras, two or more of the cameras may be identified as having captured images of the location at a time of the event. Users within the materials handling facility may be identified from images captured prior to, during or after the event, and visual representations of the respective actors may be generated from the images. The event may be associated with one of the users based on distances between the users' hands and the location of the event, as determined from the visual representations, or based on imaging data captured from the users' hands, which may be processed to determine which, if any, of such hands includes an item associated with the event.

Associating items with actors based on digital imagery

Associating events with actors based on digital imagery

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Redmond, WA, United States of America

Kartik Muktinutalapati