Target Brands, Inc.

Christopher M Brakob

Ethan Sommer

Brian R Holt

Miguel Herrera

Michael Gullickson Dietsche

Connor James Lane

Andrew J Wipf

Ryan Andrew Pekarek

Jason M Kadrmas

Melissa Marie Beuthien

Kathleen J Roush

Mauricio Donyel Hunter

Disclosed herein are tamperproof gift cards. A gift card can include: a first identifier printed in permanent and visible ink on a treated first portion of the gift card and a second identifier printed in a matrix of ink dots on a second portion that obscures the second identifier. Attempting to remove the first identifier may cause visible indicators of tampering on the first portion. The matrix can include reactive and other non-reactive ink dots that, as printed, have a same visible appearance. The second identifier can be represented by the reactive ink dots. Rubbing the matrix with a physical object can cause the reactive and non-reactive ink dots to have different physical appearances so that the second identifier becomes visible. The gift card can also include tamperproof properties applied in layers that may cause modifications to the first or second portions of the gift card to become permanently visible.

Gift card having coin reactive ink and other tamperproof properties

The disclosed technology provides for generating best images of a person in a retail environment. A method may include receiving, by an edge computing device from a camera, a continuous stream of image data of the retail environment, detecting, using object detection techniques, a person in the image data, the image data including a group of images that are part of a time series, generating bounding boxes for each of the group of images around the person based on detecting the person as they move in the images, identifying, based on applying a features model to each bounding box, at least one feature of the group of images depicting the person, selecting a subset of the bounding boxes having at least one feature that satisfies best images criteria, the subset having best images of the person, and returning the best images of the person.

Automatically generating best digital images of a person in a physical environment

Disclosed are systems and methods for determining whether an unknown product matches a scanned barcode during checkout. The system includes a checkout lane having a flatbed scanning area with scanning devices and a point of sale (POS) terminal that scans a product identifier of an unknown product, identifies a product associated with the scanned product identifier, and transmits, to a computing system, product information. An overhead camera idnentifies, based on detecting an optical signal from the POS terminal, that a scanning event occurred, captures image data of the unknown product, and transmits, to the computing system, the image data. The computing system generates machine learning product identification models for identifying unknown products, identifies candidate product identifications for the unknown product based on applying the models to the image data, and determines, based on the candidate product identifications and the information about the product, whether the unknown product matches the product.

Identifying barcode-to-product mismatches using point of sale devices and overhead cameras

The disclosed technology provides for automatically detecting and responding to potentially suspicious or risky activity in a retail environment. A method can include receiving, from monitoring devices in a retail environment, a stream of activity data, applying a model to the stream of activity data to identify a portion of the data corresponding to guest activity during a checkout process, identifying whether a risk event is associated with the activity, determining a guest risk impact score, selecting (i) a particular manual response from among candidate manual responses and (ii) a particular automated response from among candidate automated responses based on the risk impact score satisfying manual response criteria and/or automated response criteria, transmitting instructions to a POS terminal to implement the particular automated response, and/or transmitting instructions to implement the particular manual response to one or more mobile devices, that prompt employees to perform the manual response.

Risk-based adaptive responses to user activity in a retail environment

Gift card

A keyset includes a plurality of keys, a holder attached to each of the keys in the plurality of keys, an RFID tag positioned within the holder, and a barcode positioned within the holder. A system includes a server and a first handheld device configured to scan a barcode on a keyset to obtain a barcode identifier and to relay the barcode identifier to the server to check the keyset out of a key cabinet. An RFID reader is configured to receive an RFID signal from an RFID tag on the keyset to obtain an RFID identifier and to relay the RFID identifier to a second handheld device. The second handheld device is configured to receive the RFID identifier sent by the RFID reader and to determine that the keyset was detected during a scan of a key cabinet based on the received RFID identifier.

Growing community of inventors

Maple Grove, MN, United States of America

Christopher M Brakob