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 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 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 system for processing images captured in a retail store and differentiating between products with similar visual appearances is provided. The system may comprise at least one processor configured to receive at least one image depicting a store shelf having a product displayed thereon, analyze the at least one image to detect the product, determine that the detected product is either a first type of product or a second type of product, analyze the at least one image to determine a price associated with the detected product, determine that the detected product is of the first type of product when the determined price falls within a first price range associated with the first type of product, and determine that the detected product is of the second type of product when the determined price falls within a second price range associated with the second type of product.

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 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 system for processing images captured in a retail store and differentiating between products with similar visual appearances is provided. The system may comprise at least one processor configured to receive at least one image depicting a store shelf having a product displayed thereon, analyze the at least one image to detect the product, determine that the detected product is either a first type of product or a second type of product, analyze the at least one image to determine a price associated with the detected product, determine that the detected product is of the first type of product when the determined price falls within a first price range associated with the first type of product, and determine that the detected product is of the second type of product when the determined price falls within a second price range associated with the second type of product.

Abstract: This disclosure relates to systems, methods, and devices that can identify products on a shelf, and determine item descriptions and pricing from associated labels. In one embodiment, an image processing system for providing an indication about shelf label accuracy in a store is provided. The image processing system comprises at least one processor configured to receive, from a hand-held device, an image depicting products on store shelves, and associated labels coupled to the store shelves. The processor can be configured to process the image to identify at least some of the products and to access a database to determine associated product ID numbers. The processor can be further configured to determine product identifier and displayed price from the associated labels. The processor can also be configured to determine one or more product-label mismatches related to incorrect product placement on the shelf and to provide electronic notification of the mismatches.

Abstract: Methods, devices, and computer-readable storage media for providing a user with augmented guidance to capture images of products placed on a store shelving unit, the method including using an image sensor of a mobile device to capture and display in real-time a video stream depicting a store shelving unit, augmenting the video stream with a marking identifying an area of the store shelving unit and receiving an image including an area outside the marked area. A plurality of images captured by the image sensor and associated with a discontinuous first area of the store shelving unit with at least two non-overlapping regions and having image resolution higher than an image resolution of the video stream are used to mark the area of the video stream representing discontinuous first area and a second area outside the discontinuous first area. The received image overlaps the discontinuous first area and second area.