公开(公告)号：US11568632B1

公开(公告)日：2023-01-31

申请号：US17013207

申请日：2020-09-04

Applicant: Amazon Technologies, Inc.

Inventor： Sudarshan Narasimha Raghavan ,  Xiaofeng Ren ,  Michel Leonard Goldstein ,  Ohil K. Manyam

IPC: G06V20/52 ,  G06V10/75

Abstract: This disclosure describes a system for automatically identifying an item from among a variation of items of a same type. For example, an image may be processed and resulting item image information compared with stored item image information to determine a type of item represented in the image. If the matching stored item image information is part of a cluster, the item image information may then be compared with distinctive features associated with stored item image information of the cluster to determine the variation of the item represented in the received image.

公开(公告)号：US10769488B1

公开(公告)日：2020-09-08

申请号：US16520861

申请日：2019-07-24

Applicant: Amazon Technologies, Inc.

Inventor： Sudarshan Narasimha Raghavan ,  Xiaofeng Ren ,  Michel Leonard Goldstein ,  Ohil K. Manyam

IPC: G06K9/62

Abstract: This disclosure describes a system for automatically identifying an item from among a variation of items of a same type. For example, an image may be processed and resulting item image information compared with stored item image information to determine a type of item represented in the image. If the matching stored item image information is part of a cluster, the item image information may then be compared with distinctive features associated with stored item image information of the cluster to determine the variation of the item represented in the received image.

公开(公告)号：US10366306B1

公开(公告)日：2019-07-30

申请号：US14031798

申请日：2013-09-19

Applicant: Amazon Technologies, Inc.

Inventor： Sudarshan Narasimha Raghavan ,  Xiaofeng Ren ,  Michel Leonard Goldstein ,  Ohil K. Manyam

IPC: G06K9/00 ,  G06K9/62

Abstract: This disclosure describes a system for automatically identifying an item from among a variation of items of a same type. For example, an image may be processed and resulting item image information compared with stored item image information to determine a type of item represented in the image. If the matching stored item image information is part of a cluster, the item image information may then be compared with distinctive features associated with stored item image information of the cluster to determine the variation of the item represented in the received image.