Produce and bulk good management within an automated shopping environment

US2019333039A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2019333039-A1
Application numberUS-201916398098-A
CountryUS
Kind codeA1
Filing dateApr 29, 2019
Priority dateApr 27, 2018
Publication dateOct 31, 2019
Grant date

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  1. Title

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  2. Abstract

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  4. Key dates

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  5. First independent claim

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Abstract

Official abstract text for this publication.

A system and method for produce and bulk good monitoring that includes: at a computer vision monitoring system, collecting image data; detecting selection of a set of items by a first user through computer vision, the items having been displayed in an environment; applying computer vision to the image data and detecting an item identity of the set of items; collecting weight information from a scale when the item is present at the scale; and generating an item price factoring in weight information and the item identity.

First claim

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We claim: 1 . A method for produce monitoring systems comprising: at a computer vision monitoring system, collecting image data; detecting selection of a set of items by a first user through computer vision, the items having been displayed in an environment; applying computer vision to the image data and detecting an item identity of the set of items; collecting weight information from a scale when the item is present at the scale; and generating an item price factoring in weight information and the item identity. 2 . The method of claim 2 , further comprising detecting when the item is present at the scale through computer vision. 3 . The method of claim 1 , further comprising communicating an added item request with the item identifier and the item price to a point of sale system. 4 . The method of claim 3 , wherein collecting weight information comprises collecting weight information from the scale, which is integrated into the point of sale system. 5 . The method of claim 1 , wherein collecting weight information comprises collecting weight information from the scale positioned on the sales area of the environment. 6 . The method of claim 5 , wherein the scale is a network-connected scale; and wherein collecting weight information from the scale positioned comprises, at the scale, communicating a measured weight to the computer vision monitoring system; and matching the communicated weight to the set of items. 7 . The method of claim 5 , wherein the scale has a visual display of weight; wherein the scale is communicatively decoupled from the monitoring system; and wherein collecting weight information from the scale comprises extracting a displayed weight on the visual display of the weight. 8 . The method of claim 7 , further comprising, at the scale, displaying the visual display of the weight in a graphical machine-readable code. 9 . The method of claim 5 , further comprising at a the computer vision monitoring system, communicating item identity to a printer; and at the printer, printing an item price tag with associated information of the item identifier and the weight information. 10 . The method of claim 1 , wherein the scale is part of display unit storing the items prior to selection; and wherein the display unit holds multiple types of items. 11 . The method of claim 10 , wherein collecting weight information is performed upon detecting a decrease in weight. 12 . The method of claim 10 , wherein during applying computer vision processing of the image data and detecting an addition of the set of items to the display unit during a stocking event; and wherein collecting weight information comprises detecting a weight change when detecting the addition of the set of items to the display unit and assigning the weight information to the set of items detected through computer vision. 13 . The method of claim 1 , further comprising: generating a volumetric estimation from the collected image data of the set of items and generating a predicted weight; if the set of item is not detected at the scale, setting the predicted weight as the weight when generating the item price. 14 . The method of claim 1 , further comprising: detecting selection of a second set of items from storage by the first user through computer vision; applying computer vision to the image data and detecting a second item identity of the second set of items; generating a volumetric estimation from the collected image data of the second set of items and generating a predicted weight; generating a second item price of the second set of items factoring in the predicted weight and the second item identity. 15 . The method of claim 14 , wherein generating a volumetric estimation from the collected image data of the second set of items comprises through computer vision processing: estimating volume of a first collection of items at a time prior to removal of the second set of items, detecting removal of the second set of items from the first collection of items, estimating volume of the first collection of items after removal of the second set of items; and generating a predicted weight of the second set of items based on a change in the estimated volume of the first collection of items. 16 . The method of claim 14 , wherein generating a volumetric estimation from the image data of the second set of items comprises, for each item in the second set of items, generating an individual volumetric estimation of volume. 17 . The method of claim 14 , wherein generating a volumetric estimation from the image data of the second set of items comprises generating a simulated volumetric prediction of the set of items. 18 . The method of claim 1 , wherein collecting image data comprises collecting image data from a plurality of image capture devices oriented with an aerial view and distributed at distinct regions across the environment. 19 . The method of claim 1 , further comprising adding a product line item to a checkout list managed through the CV monitoring system. 20 . A machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations in connection with a computer vision monitoring system comprising: collecting image data; detecting selection of a set of items by a first user through computer vision, the items having been displayed in an environment; applying computer vision to the image data and detecting an item identity of the set of items; collecting weight information from a scale when the item is present at the scale; and generating an item price factoring in weight information and the item identity. 21 . A system for bulk good monitoring systems comprising a computer vision monitoring system configured to collect image data of users and items in a shopping environment; and a computer vision processing system configured to: detect selection by a user of a set of items displayed in the shopping environment, apply computer vision to the image data and detecting an item identity of the set of items, collect weight information from a scale when the item is present at the scale, and generate an item price factoring in weight information and the item identity.

Assignees

Inventors

Classifications

  • G06Q20/12Primary

    specially adapted for electronic shopping systems · CPC title

  • Point-of-sale [POS] network systems · CPC title

  • G06Q20/201Primary

    Price look-up processing, e.g. updating · CPC title

  • Input by product or record sensing, e.g. weighing or scanner processing · CPC title

  • Specified transaction journal output feature, e.g. printed receipt or voice output · CPC title

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What does patent US2019333039A1 cover?
A system and method for produce and bulk good monitoring that includes: at a computer vision monitoring system, collecting image data; detecting selection of a set of items by a first user through computer vision, the items having been displayed in an environment; applying computer vision to the image data and detecting an item identity of the set of items; collecting weight information from a …
Who is the assignee on this patent?
Grabango Co
What technology area does this patent fall under?
Primary CPC classification G06Q20/12. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Oct 31 2019 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).