-
公开(公告)号:US11010903B1
公开(公告)日:2021-05-18
申请号:US16262685
申请日:2019-01-30
Applicant: Amazon Technologies, Inc.
Inventor: Elisha Gallaudet , Timothy Stallman
Abstract: 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.
-
公开(公告)号:US11769110B1
公开(公告)日:2023-09-26
申请号:US16752546
申请日:2020-01-24
Applicant: Amazon Technologies, Inc.
Inventor: Jane Margaret Bourke , Elisha Gallaudet , Cara Held , Brandon Kwok , Nan Ma , Audra Snider Merkel , Bradley John Saviello , Megan Tranter , Steven Wilson
IPC: G06Q10/087 , G06Q10/0631
CPC classification number: G06Q10/087 , G06Q10/0631 , G06Q10/063112
Abstract: 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.
-