Amazon Technologies, Inc.

Elisha Gallaudet

Timothy Stallman

Steven Augustine Wilson

Jane Margaret Bourke

Audra Snider Merkel

Cara Held

Bradley John Saviello

Nan Ma

Megan Tranter

Brandon Kwok

Systems and methods are provided herein for performing one or more actions based on kinematic data. An operator management module may obtain video input data depicting a two-dimensional representation of a subject during performance of an activity. A set of points of the subject may be identified based at least in part on a machine-learning model. A 3D representation of the subject may be generated based at least in part on the points identified. Kinematic data related to the subject may be generated utilizing the 3D representation of the subject. Any suitable number of suggested actions may be performed based at least in part on the kinematic data.

Systems and methods for operator motion management

Techniques are described for processing digital video data using one or more machine learning models to determine an outcome of an item placement operation within a fulfillment center environment. Video data is processed using one or more machine learning models to determine an estimated likelihood that an occurrence of a particular fulfillment center operation is depicted within the two or more instances of digital video data. Upon determining that the estimated likelihood exceeds a predefined threshold confidence level, the video data is processed using second one or more machine learning models to determine a bin placement prediction and a confidence value. A data repository for a control system for the fulfillment center environment is updated, based on the bin placement prediction and the confidence value.

Computer vision and machine learning techniques for item tracking

Growing community of inventors

Andover, MA, United States of America

Elisha Gallaudet