Abstract: A system for processing images captured in a retail store is provided. The system may include a processor configured to: access a database storing a group of product models; receive an image depicting at least part of a store shelf having a plurality of products of a same type displayed thereon; analyze the image and determine a first candidate type of the products based on the group of product models and the image analysis; determine a first confidence level associated with the first candidate type; when the first confidence level is below a confidence threshold, determine a second candidate type of the products using contextual information; determine a second confidence level associated with the determined second candidate type of the plurality of products; and when the second confidence level is above the confidence threshold, initiate an action to update the group of product models stored in the database.

Abstract: Methods, systems, and computer-readable media are provided for selecting items for presentation on electronic visual displays in retail stores. In one implementation, a method may comprise: obtaining a plurality of images of products in a retail store; analyzing a first image to determine whether products of a particular product type are available at a first point in time; analyzing a second image to determine whether products of the particular product type are available at a second point in time; and based on the determination of whether products of the particular product type are available at the first point in time and the determination of whether products of the particular product type are available at the second point in time, selecting whether to display a particular item on an electronic visual display in the retail store.

Abstract: A non-transitory computer-readable medium includes instructions that when executed by a processor cause the processor to perform a method for assessing quality of tasks performed by persons in retail stores. The method may include receiving an indication that a person completed a task corresponding to at least one shelf in a retail store. The method may also include receiving at least one image of the at least one shelf, the at least one image being captured using an image sensor after the completion of the task. The method may further include analyzing the at least one image to determine at least one property associated with performing the task. The method may further also using the at least one property to determine a reward for performing the task.

Abstract: A method for triggering image processing based on vibration data analysis may include receiving vibration data captured using a vibration sensor mounted to a shelving unit including; analyzing the vibration data to determine whether a vibration is a result of an engagement of a person with a retail shelf; in response to a determination that the vibration is the result of the engagement of the person with the retail shelf, triggering analysis of an image of captured after the beginning of the engagement of the person with the retail shelf; in response to a determination that the vibration is not the result of the engagement of the person with the retail shelf, forgoing triggering the analysis of the image; and providing information based on a result of the analysis of the image.

Abstract: Systems and methods are provided for retail environments. In one implementation, a non transitory computer-readable medium may include instructions that when executed by a processor cause the processor to perform a method. The method may include detecting online digital activities related to a retail store and originating from customers in the retail store; receiving position information indicating positions from which the detected online digital activities originated; clustering the detected online digital activities based on the position information to provide clusters of detected online digital activities, each cluster being associated with a different region of the retail store; using an image acquisition device to capture images of a particular region of the retail store associated with a particular cluster; analyzing the images to detect a condition of the retail store associated with the detected cluster; and automatically initiating a remedial action to address the detected condition.

Abstract: Methods, systems, and computer-readable media are provided for customized presentation of items on electronic visual displays in retail stores. In one implementation, a method may comprise: obtaining a plurality of images of products in a retail store captured; analyzing a first image to determine whether products of a particular product type are available at a first point in time; analyzing a second image to determine whether products of the particular product type are available at a second point in time; based on the determination of whether products of the particular product type are available at the first point in time and the determination of whether products of the particular product type are available at the second point in time, selecting at least one display parameter for a particular item; and using the selected at least one display parameter to display the particular item on an electronic visual display.

Abstract: A method for using an electronic shopping list to resolve ambiguity associated with a selected product may include accessing an electronic shopping list associated with a customer of a retail store; receiving image data captured using one or more image sensors in the retail store; analyzing the image data to detect a product selection event involving a shopper; identifying a product associated with the detected product selection event based on analysis of the image data and further based on the electronic shopping list; and based on the identification of the product, updating a virtual shopping cart associated with the shopper.

Abstract: A system for processing images captured in a retail store and automatically identifying misplaced products is provided. The system may comprise at least one processor configured to receive one or more images captured by one or more image sensors from an environment of a retail store, detect in the one or more images a first product, determine that the first product is not located in the first correct display location, cause an issuance of a user-notification associated with the first product, detect in the one or more images a second product, determine that the second product is not located in the second correct display location, and after determining that the second product is not located in the second correct display location and when the second urgency level is lower than the first urgency level, withhold issuance of a user-notification associated with the second product.

Abstract: A method may include analyzing first images to determine an actual placement of first products displayed on shelves of a retail store; determining a deviation of an actual placement of some of the first products from the desired placement of products associated with a first planogram; receiving second images; analyzing the second images to determine an actual placement of the second products displayed on the shelves; identifying a deviation of the actual placement of some of the second products from the desired placement of products associated with the first planogram; using the second planogram to determine whether an arrangement associated with a second products conforms to the second planogram rather than to the first planogram; and when the arrangement associated with the second products conforms to the second planogram, avoiding issuance of a notification indicating a deviation relative to the first planogram.

Abstract: A system for automatically identifying situations to withhold planogram incompliance notifications in a retail store is disclosed. The system has a processor that receives image data depicting products displayed on a store shelf from image sensors mounted in the retail store. The processor identifies a product type associated with the displayed products and determines a placement of products of that product type on the shelf. The processor accesses a planogram describing a desired placement of products and identifies, based on the planogram, a discrepancy between the determined placement of products and the desired placement of product. The processor determines whether a notice-override condition exists. If a notice-override condition exists, the processor, withholds issuance of a user-notification associated with the identified discrepancy. If a notice-override condition does not exist, the processor issues the user-notification associated with the identified discrepancy.

Abstract: A system for processing images captured in a retail store is provided. The system may include a processor configured to: access a database storing a group of product models; receive an image depicting at least part of a store shelf having a plurality of products of a same type displayed thereon; analyze the image and determine a first candidate type of the products based on the group of product models and the image analysis; determine a first confidence level associated with the first candidate type; when the first confidence level is below a confidence threshold, determine a second candidate type of the products using contextual information; determine a second confidence level associated with the determined second candidate type of the plurality of products; and when the second confidence level is above the confidence threshold, initiate an action to update the group of product models stored in the database.

Abstract: A method for identifying products removed from bulk packaging includes receiving one or more images acquired by a camera arranged to capture interactions between a shopper and one or more bulk packages each configured to contain a plurality of products, analyzing the one or more images to identify the shopper and a particular bulk package among the one or more bulk packages with which the identified shopper interacted, receiving an output from at least one sensor configured to monitor changes associated with the particular bulk package, analyzing the output to determine a quantity of products removed from the particular bulk package by the identified shopper, and updating a virtual shopping cart associated with the identified shopper to include the determined quantity of products and an indication of a product type associated with the particular bulk package.

Abstract: An apparatus for securing a camera to a retail shelving unit is disclosed. The apparatus may have a pair of opposing securing surfaces for securing the apparatus to a support element of the retail shelving unit. The pair of opposing securing surfaces may form a gap between the pair of opposing securing surfaces. The gap may be configured to accept the support element of the retail shelving unit. The apparatus may also have an arm extending from one of the pair of opposing securing surfaces and having a distal end. The distal end may have a camera support area including a least one opening.

Abstract: A system for identifying products in a retail store is provided. The system may include a processor configured to: receive an image depicting a store shelf and a product displayed thereon; select a product model subset based on a characteristic of the store shelf determined based on analysis of the image; determine whether the product model subset is applicable to the product; and when the product model subset is applicable to the product, analyze a representation of the product depicted in the image using the product model subset, and identify the product based on the analysis of the representation of the product.

Abstract: A system for processing images captured in a retail store and automatically identifying products displayed on shelving units, includes at least one processor configured to: receive a first image depicting a shelving unit with a plurality of products of differing product types displayed thereon and a first plurality of labels coupled to the shelving unit; receive a set of second images depicting a second plurality of labels; correlate a first label depiction of a specific label included in the first image to a second label depiction of the same specific label included in a second image; use information derived from the second label depiction to determine a type of products displayed in the first image in proximity to the specific label; and initiate an action based on the determined type of products displayed in proximity to the specific label.

Abstract: Systems and methods are provided for retail environments. In one implementation, a non transitory computer-readable medium may include instructions that when executed by a processor cause the processor to perform a method. The method may include receiving, from first sensors first sensed data indicating selection of a first product by a customer; determining, from the first sensed data, a first property associated with the first product; issuing a first query to the customer regarding the first property and, in response, receiving first information from the customer; comparing the first information with the first property; determining, based on the comparison, an integrity indicator associated with the customer; receiving, from second sensors second sensed data indicating a selection of a second product by the customer; determining, based on the integrity indicator, at least one action to determine a second property associated with the second product; and initiating the at least one action.

Abstract: Systems and methods are provided for retail environments. In one implementation, a non transitory computer-readable medium may include instructions that when executed by a processor cause the processor to perform a method. The method may include detecting online digital activities related to a retail store and originating from customers in the retail store; receiving position information indicating positions from which the detected online digital activities originated; clustering the detected online digital activities based on the position information to provide clusters of detected online digital activities, each cluster being associated with a different region of the retail store; using an image acquisition device to capture images of a particular region of the retail store associated with a particular cluster; analyzing the images to detect a condition of the retail store associated with the detected cluster; and automatically initiating a remedial action to address the detected condition.

Abstract: A method for identifying products removed from bulk packaging includes receiving one or more images acquired by a camera arranged to capture interactions between a shopper and one or more bulk packages each configured to contain a plurality of products, analyzing the one or more images to identify the shopper and a particular bulk package among the one or more bulk packages with which the identified shopper interacted, receiving an output from at least one sensor configured to monitor changes associated with the particular bulk package, analyzing the output to determine a quantity of products removed from the particular bulk package by the identified shopper, and updating a virtual shopping cart associated with the identified shopper to include the determined quantity of products and an indication of a product type associated with the particular bulk package.

Abstract: A system for identifying products in a retail store is provided. The system may include a processor configured to: receive an image depicting a store shelf and a product displayed thereon; select a product model subset based on a characteristic of the store shelf determined based on analysis of the image; determine whether the product model subset is applicable to the product; and when the product model subset is applicable to the product, analyze a representation of the product depicted in the image using the product model subset, and identify the product based on the analysis of the representation of the product.

Abstract: A system for identifying perishable products in a retail store based on analysis of image data and for automatically generating suggestions relating to the identified products is provided. The system may comprise at least one processor configured to: receive a set of images depicting a plurality of perishable products displayed on at least one shelving unit in a retail store; analyze the set of images to determine information about a displayed inventory of the plurality of perishable products; obtain information about additional perishable products scheduled to be displayed on the at least one shelving unit; use the information about the displayed inventory and the information about the additional perishable products to determine at least one suggestion regarding placement of perishable products in the retail store; and provide the at least one suggestion to an entity associated with the retail store.