Machine learning methods and system for tracking label coded items in a retail store for cashier-less transactions
First Claim
1. A method for identifying actions in a retail store, comprising:
- sampling a shopping environment by receiving by one or more processing entities associated with the store, output of one or more sensors disposed in the retail store, each sensor capable of producing said output as raw data reflecting an exposure of said each sensor to a scenario occurring within a sensing range of said each sensor in the retail store;
processing, by said one or more processing entities associated with the retail store, at least one sensor output to generate at least one extracted feature;
processing said at least one extracted feature, by said one or more processing entities associated with the retail store together with output from said one or more sensors disposed in the retail store, to produce feature input to a machine learning model to generate a label characterizing a state of the scenario occurring in the retail store, the state identifying interactions by a shopper as a take of an item from a shelf, the interactions of the shopper include a reach toward the shelf to perform the take of the item, the state of the scenario includes identification data of the item taken from the shelf.
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Abstract
Devices, systems, and method are provided for operating a store. One method includes sampling a shopping environment using one or more sensors to produce features relating to a state of activity of the store. The method further includes processing output of at least one sensor through a feature extractor to extract one or more additional features relating to the state of activity of the retail store. Then, processing at least part of the produced features and at least part of the extracted additional features using a processing entity associated with the store and a machine learning model to generate one or more labels relating to the state of activity of the retail store. In further embodiments, items in the store are physically taken into possession and automatically added to a user'"'"'s electronic shopping cart to enable processing of a cashier-less transaction.
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Citations
20 Claims
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1. A method for identifying actions in a retail store, comprising:
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sampling a shopping environment by receiving by one or more processing entities associated with the store, output of one or more sensors disposed in the retail store, each sensor capable of producing said output as raw data reflecting an exposure of said each sensor to a scenario occurring within a sensing range of said each sensor in the retail store; processing, by said one or more processing entities associated with the retail store, at least one sensor output to generate at least one extracted feature; processing said at least one extracted feature, by said one or more processing entities associated with the retail store together with output from said one or more sensors disposed in the retail store, to produce feature input to a machine learning model to generate a label characterizing a state of the scenario occurring in the retail store, the state identifying interactions by a shopper as a take of an item from a shelf, the interactions of the shopper include a reach toward the shelf to perform the take of the item, the state of the scenario includes identification data of the item taken from the shelf. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. A method for identifying actions in a store, comprising:
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sampling a shopping environment using one or more sensors; and using a processing entity associated with the store for processing features related to the sampled shopping environment, the features are output from the one or more sensors using one or more machine learning classifiers and are further processed to derive one or more labels that classify activity of a shopper as the shopper moves about the store; wherein at least one processing entity associated with the store detects from said activity that an item of the store has been taken by the shopper, the taken item being added to an electronic shopping cart associated to an account linked to the shopper detected to be interacting with the item; wherein at least one sensor is a camera producing output including image data capturing one or more codes of items present in the store, said image data processed by said at least one processing entity to extract an ID associated with said item, wherein said item being one by which the shopper is identified to be interacting with and in response to detecting the shopper reaching toward a shelf to perform the take of the item, an inference is made reflecting a state of a shopping scenario, the inference made characterizes the shopping scenario involving the shopper, the taking of the item, and the item taken from the shelf, wherein the item determined to be taken is added to the electronic shopping cart. - View Dependent Claims (17, 18, 19, 20)
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Specification