Abstract: Systems and methods of monitoring inventory of a product storage facility include an image capture device configured to move about the product storage areas of the product storage facility and capture images of the product storage areas from various angles. A computing device coupled to the image capture device obtains the images of the product storage areas captured by the image capture device and processes the obtained images of the product storage areas to detect individual products captured in the obtained images. Based on detection of the individual products captured in the images, the computing device analyzes each of the obtained images to extract meta data from the packaging the individual products to detect one more keywords and determine the locations of the detected keywords on the packaging, and then utilize this information to predict an identity of the products associated with the packaging.

Abstract: In some embodiments, apparatuses and methods are provided to support individuals in a retail environment. Some embodiments, provide systems, comprising: a plurality of cameras positioned in a retail store; an image processing control circuit configured to determine a customer field of view; a product identification control circuit configured to identify a set of multiple products within the identified customer field of view, assign a viewing probability to each product without the first customer having to touch the first product; a product selection control circuit configured to determine a purchase probability of the first product; add the first product to a virtual electronic cart when the purchase probability of the first product exceeds a purchase probability threshold; and communicate instructions to control the worker personal computing device to instruct a worker to retrieve the first product.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to processing captured images. In some embodiments, there is provided a system for processing captured images of objects at a product storage facility including a trained machine learning model; and a control circuit. The control circuit may group a plurality of product identifiers into one or more clusters based on at least one of visual similarity of corresponding images, textual similarity of corresponding associated descriptions, and associated relationships between product identifiers of the plurality of product identifiers; determine clusters having common elements that are at least within a similarity threshold of each other; merge the clusters with the common elements; and generate a mapping dataset used to retrain the trained machine learning model to identify a plurality of objects. The mapping dataset may include a plurality of associations of associated product identifiers to a single object.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to processing captured images. In some embodiments, there is provided a system for processing captured images of objects at a product storage facility including a trained machine learning model; and a control circuit. The control circuit may identify a product identifier associated with an object in a captured image; generate predicted product identifiers associated with the object in the captured image based on text identified from the object in the captured image; aggregate the predicted product identifiers; determine a feature of the objects associated with the aggregated predicted product identifiers; determine one or more confusing product identifiers based on a determination of the aggregated predicted product identifiers being associated with the feature; and update a dataset with at least one of the one or more confusing product identifiers and images associated with the one or more confusing product identifiers.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to processing captured images. In some embodiments, there is provided a system for processing captured images of objects including a memory and a control circuit executing a trained machine learning model. The memory may be configured to store a plurality of images comprising first images and second images. The control circuit may be configured to: allocate each of the first images into one of a plurality of datasets; cluster each image in the dataset into one of a plurality of groups; select a sample from at least one of the plurality of groups; cluster each of the second images into one of dominant product identifier group and a non-dominant product identifier group; select a sample from the dominant product identifier group and a sample from the non-dominant product identifier group; and output the selected sample.

Abstract: Systems and methods of updating templates for use in recognizing individual products in images captured at a product storage facility include an image capture device that captures one or more images of product storage structure at a product storage facility, a computing device in communication with the image capture device, and an electronic database that stores keyword model templates and feature model templates associated with images of previously recognized individual products detected at the product storage facility.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to processing captured images of objects at a product storage facility. In some embodiments, there is provided a system for processing captured images of objects including a trained machine learning model and a control circuit. In some embodiments, the trained machine learning model is configured to process unprocessed captured images. In some embodiments, the control circuit is configured to associate each of the processed images into one of a first group, a second group, or a third group; remove at least one processed image associated with the first group from the processed images in accordance with a first processing rule; and output remaining processed images associated with the first group and processed images associated with the second group to be used to retrain the trained machine learning model.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to labeling objects in captured images. In some embodiments, there is provided a system for labeling objects in images captured at a product storage facility including a control circuit and a user interface. The control circuit is configured to select a set of unprocessed images; receive a selected configuration based on data resulting from iteratively processing the set of unprocessed images; cluster each unprocessed image into a corresponding group based on the selected configuration; select a plurality of clustered images from each of the plurality of groups; and output the plurality of clustered images from each group. The user interface is configured to: display each clustered image; and receive a user input labeling one or more objects shown in each clustered image resulting in a labeled dataset used to train a machine learning model.

Abstract: Systems and methods of creating reference template images for detecting and recognizing products at a product storage facility include an image capture device having a field of view that includes a product storage structure of the product storage facility, and a computing device including a control circuit and being communicatively coupled to the image capture device. The computing device obtains images of the product storage structure captured by the image capture device, analyzes the obtained images to detect individual ones of the products located on the product storage structure. Then, the computing device identifies the individual ones of the products detected in the images and crops each of the individual ones of the identified products from the images to generate cropped images. The computing device then creates a cluster of the cropped images, and selects one of the cropped images as a reference template image of an identified individual product.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to updating inventory of products. In some embodiments, there is provided a system for updating inventory of products including a database; at least one image capture device; and a control circuit. The control circuit is configured to: process an image by: detecting units of one or more products in the image; grouping each detected unit into one or more clusters based on at least one of textual similarities, visual similarities, geometrical similarities, or relative spatial distance; detecting a product identifier for each cluster; identifying a product corresponding to the detected product identifier of each cluster; and counting the detected units associated with each cluster. The control circuit is configured to cause an update to the inventory of products in the database based on the counted detected units of each cluster.

Abstract: Systems and methods of monitoring inventory of a product storage facility include an image capture device configured to move about the product storage areas of the product storage facility and capture images of the product storage areas from various angles. A computing device coupled to the image capture device obtains the images of the product storage areas captured by the image capture device and processes the obtained images of the product storage areas to detect individual products captured in the obtained images. Based on detection of the individual products captured in the images, the computing device analyzes each of the obtained images to extract meta data from the packaging the individual products to detect one more keywords and determine the locations of the detected keywords on the packaging, and then utilize this information to predict an identity of the products associated with the packaging.

Abstract: In some embodiments, apparatuses and methods are provided to support individuals in a retail environment. Some embodiments, provide systems, comprising: a plurality of cameras positioned in a retail store; an image processing control circuit configured to determine a customer field of view; a product identification control circuit configured to identify a set of multiple products within the identified customer field of view, assign a viewing probability to each product without the first customer having to touch the first product; a product selection control circuit configured to determine a purchase probability of the first product; add the first product to a virtual electronic cart when the purchase probability of the first product exceeds a purchase probability threshold; and communicate instructions to control the worker personal computing device to instruct a worker to retrieve the first product.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to ensuring quality of meat cuts. In some embodiments, a system for ensuring quality of meat cuts comprises a capture device comprising an image capture device configured to capture an image of a cut of meat, a depth sensor configured to capture depth data, a transceiver configured to transmit the image and the depth data, a microcontroller configured to control the image capture device, the depth sensor, and the transceiver, a database configured to store meat cut specifications, and the control circuit configured to receive, from the capture device, the image and the depth data, retrieve, from the database, a meat cut specification, evaluate the image of the cut of meat and the depth data associated with the cut of meat, and classify the cut of meat.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to presenting packing instructions to a user. In some embodiments, a system for presenting packing instructions to a user comprises a database configured to store packing information and item visualizations, wherein the packing information includes placements of items in orders in containers, and wherein the item visualizations depict appearances of items sold by the retailer, a control circuit configured to receive an order identifier for an order, retrieve packing information associated with the order and item visualizations for the items in the order, generate a packing visualization for the order, wherein the packing visualization for the order depicts placement of the items in the order in the container, transmit, to a display device for presentation, the packing visualization for the order, and a display device configured to present the packing visualization for the order to the user.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to presenting packing instructions to a user. In some embodiments, a system for presenting packing instructions to a user comprises a database configured to store packing information and item visualizations, wherein the packing information includes placements of items in orders in containers, and wherein the item visualizations depict appearances of items sold by the retailer, a control circuit configured to receive an order identifier for an order, retrieve packing information associated with the order and item visualizations for the items in the order, generate a packing visualization for the order, wherein the packing visualization for the order depicts placement of the items in the order in the container, transmit, to a display device for presentation, the packing visualization for the order, and a display device configured to present the packing visualization for the order to the user.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to ensuring quality of meat cuts. In some embodiments, a system for ensuring quality of meat cuts comprises a capture device comprising an image capture device configured to capture an image of a cut of meat, a depth sensor configured to capture depth data, a transceiver configured to transmit the image and the depth data, a microcontroller configured to control the image capture device, the depth sensor, and the transceiver, a database configured to store meat cut specifications, and the control circuit configured to receive, from the capture device, the image and the depth data, retrieve, from the database, a meat cut specification, evaluate the image of the cut of meat and the depth data associated with the cut of meat, and classify the cut of meat.

Abstract: In some embodiments, a system for remotely purchasing perishable products includes a plurality of image capture devices configured to capture images of perishable products, a product image database, a product attribute database, and a control circuit configured to execute computer program modules. An image processing module receives and processes images from the image capture devices to form a composite image. A product identification module identifies and segments the products in the composite image. A product selection module causes an application executed on a remote electronic device operated by a customer to display the composite image and receives from the application a selection of a product to purchase, at least one product attribute, and a quantity of individual product units to purchase. The product selection module identifies the individual product units having the selected product attribute(s) and outputs signaling to cause retrieval of the individual product units.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to ensuring quality of meat cuts. In some embodiments, a system for ensuring quality of meat cuts comprises a capture device comprising an image capture device configured to capture an image of a cut of meat, a depth sensor configured to capture depth data, a transceiver configured to transmit the image and the depth data, a microcontroller configured to control the image capture device, the depth sensor, and the transceiver, a database configured to store meat cut specifications, and the control circuit configured to receive, from the capture device, the image and the depth data, retrieve, from the database, a meat cut specification, evaluate the image of the cut of meat and the depth data associated with the cut of meat, and classify the cut of meat.

Abstract: In some embodiments, apparatuses and methods are provided to support handicapped and other customers in a retail store. Some embodiments, provide systems, comprising: a plurality of cameras positioned in a retail store; an image processing control circuit configured to determine a customer field of view; a product identification control circuit configured to identify a set of multiple products within the identified customer field of view, assign a viewing probability to each product without the first customer having to touch the first product; a product selection control circuit configured to determine a purchase probability of the first product; add the first product to a virtual electronic cart when the purchase probability of the first product exceeds a purchase probability threshold; and communicate instructions to control the worker personal computing device to instruct a worker to retrieve the first product.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to presenting packing instructions to a user.