公开(公告)号：US20240013633A1

公开(公告)日：2024-01-11

申请号：US18470059

申请日：2023-09-19

Applicant: Target Brands, Inc.

Inventor： Christopher Brakob ,  Ethan Sommer ,  Arun Patil ,  Dharmavaram Arbaaz ,  Arun Vaishnav ,  Prakash Mall ,  Neha Dixit

IPC: G07G1/00 ,  G07G3/00 ,  G06V10/764 ,  G06V20/52 ,  G06F18/2413

CPC classification number: G07G1/0045 ,  G07G3/003 ,  G06V10/764 ,  G06V20/52 ,  G06F18/24137 ,  G06F18/24147

Abstract: Disclosed herein are systems and methods for determining whether an unknown product matches a scanned barcode during a checkout process. An edge computing device or other computer system can receive, from an overhead camera at a checkout lane, image data of an unknown product that is placed on a flatbed scanning area, identify candidate product identifications for the unknown product based on applying a classification model and/or product identification models to the image data, and determine based on the candidate product identifications, whether the unknown product matches a product associated with a barcode that is scanned at a POS terminal in the checkout lane. The classification model can be used to determine n-dimensional space feature values for the unknown product and determine which product the unknown product likely matches. The product identification models can be used to determine whether the unknown product is one of the products that are modeled.

公开(公告)号：US20240220957A1

公开(公告)日：2024-07-04

申请号：US18142393

申请日：2023-05-02

Applicant: Target Brands, Inc.

Inventor： Arun Patil ,  Ashok Jayasheela ,  Arun Vaishnav ,  Kumar Abhishek ,  Spoorti Nayak ,  Dharmavaram Arbaaz

IPC: G06Q20/20 ,  G06T7/194 ,  G06T7/20 ,  G06T7/70 ,  G06V10/25 ,  G06V40/10

CPC classification number: G06Q20/208 ,  G06T7/194 ,  G06T7/20 ,  G06T7/70 ,  G06V10/25 ,  G06V40/10 ,  G06V2201/07

Abstract: The present disclosure is directed to an artificial intelligence (AI) assisted monitoring system that uses cameras to recognize a product being moved by the user across the self-checkout unit and verifying whether the product was scanned at the point-of-sale terminal based on timestamp information associated with when the product was moved across the self-checkout unit to identify miss scan thefts.

公开(公告)号：US11798380B2

公开(公告)日：2023-10-24

申请号：US17856083

申请日：2022-07-01

Applicant: Target Brands, Inc.

Inventor： Christopher Brakob ,  Ethan Sommer ,  Arun Patil ,  Dharmavaram Arbaaz ,  Arun Vaishnav ,  Prakash Mall ,  Neha Dixit

IPC: G07G1/00 ,  G06F18/2413 ,  G07G3/00 ,  G06V10/764 ,  G06V20/52

CPC classification number: G07G1/0045 ,  G06F18/24137 ,  G06F18/24147 ,  G06V10/764 ,  G06V20/52 ,  G07G3/003

Abstract: Disclosed herein are systems and methods for determining whether an unknown product matches a scanned barcode during a checkout process. An edge computing device or other computer system can receive, from an overhead camera at a checkout lane, image data of an unknown product that is placed on a flatbed scanning area, identify candidate product identifications for the unknown product based on applying a classification model and/or product identification models to the image data, and determine based on the candidate product identifications, whether the unknown product matches a product associated with a barcode that is scanned at a POS terminal in the checkout lane. The classification model can be used to determine n-dimensional space feature values for the unknown product and determine which product the unknown product likely matches. The product identification models can be used to determine whether the unknown product is one of the products that are modeled.

公开(公告)号：US20230005342A1

公开(公告)日：2023-01-05

申请号：US17856083

申请日：2022-07-01

Applicant: Target Brands, Inc.

Inventor： Christopher Brakob ,  Ethan Sommer ,  Arun Patil ,  Dharmavaram Arbaaz ,  Arun Vaishnav ,  Prakash Mall ,  Neha Dixit

IPC: G07G1/00 ,  G07G3/00 ,  G06V20/52 ,  G06V10/764 ,  G06K9/62

Abstract: Disclosed herein are systems and methods for determining whether an unknown product matches a scanned barcode during a checkout process. An edge computing device or other computer system can receive, from an overhead camera at a checkout lane, image data of an unknown product that is placed on a flatbed scanning area, identify candidate product identifications for the unknown product based on applying a classification model and/or product identification models to the image data, and determine based on the candidate product identifications, whether the unknown product matches a product associated with a barcode that is scanned at a POS terminal in the checkout lane. The classification model can be used to determine n-dimensional space feature values for the unknown product and determine which product the unknown product likely matches. The product identification models can be used to determine whether the unknown product is one of the products that are modeled.