Target Brands, Inc.

Nicholas Lojewski

Todd A Hagen

Arne Wilkin

John Ojanen

Donnie Scott Tolbert

Yeshwanth Gowda

Yeshwanth M Gowda

Richard Ryan Walstrom

Miguel Herrera

Arnab Pal

Matthew Levy

Donnie Tolbert

Surjeet Bhoora

Alexandros Glitsos

Disclosed are systems, methods, and techniques for combinable gift card components during a checkout process in a retail environment. A gift card can include a first gift card component of a first type, the first gift card component including a first identifier (e.g., barcode), and a second gift card component of a second type that can be different from the first type and separate from the first gift card component, having a second identifier. The first and second identifiers can be scanned and used to associate the first gift card component with the second gift card component. The second gift card component can be an envelope or sleeve that can be a similar size and/or a similar shape as the first gift card component. The second gift card component can permanently attach to the first gift card component during the checkout process to form the gift card.

Combinable gift card components and process for activation and validation of assembled gift cards

Disclosed are systems and techniques for determining out of stock conditions on shelves. The techniques can include receiving, by a computing system, image data from a camera having pixel locations that each uniquely address and store a pixel value, generating a backing map having cell locations that each uniquely address and share a unique address with a corresponding pixel location in the image data, each cell location storing a backing value being an empty value if the pixel value is classified as showing the backing of a shelf and the backing value being a nonempty value if the pixel value is classified as not showing the backing of the shelf, determining, in the backing map, a shelf area representing a location of the captured shelf, and identifying an empty area by finding an area above the shelf area containing a threshold number of cell locations storing the empty value.

Mobile apparatus with computer vision elements for classifying shelf-space

Described herein are systems and techniques for imaging inventory objects in an environment. A system can include a cart, a first fixed camera fixedly mounted on the cart at a first angle, a pan-tilt-zoom (PTZ) camera controllably mounted on the cart, a PTZ controller, and a cart controller. The PTZ controller can receive PTZ instructions from the cart controller and send engagement instructions to the PTZ camera. The cart controller can receive, from the first fixed camera, first image data that captures a first inventory object, determine, from the first image data, a spatial location of a first inventory object, generate PTZ instructions to cause the PTZ camera to capture the first inventory object, transmit the PTZ instructions to the PTZ controller, and receive PTZ image data that captures the first inventory object.

Mobile apparatus with computer vision elements for inventory condition

Disclosed are systems and techniques for identifying product identifiers in images. A technique can include receiving, by an edge computing device, x and y coordinates for a location of an out of stock shelf section, determining a frame of reference (FOR) based on the coordinates, the FOR including a location of a product identifier for the out of stock shelf section, determining incremental adjustments to a camera based on the FOR, instructing the camera to adjust by the incremental adjustments and capture an image of the location of the product identifier, performing image analysis on the image to identify the product identifier, determining second incremental adjustments to the camera to focus the camera on the location of the product identifier if the product identifier is not identifiable in the image, and instructing the camera to reset to original camera settings if the product identifier is identifiable in the image.

Mobile apparatus with computer vision elements for product identifier detection with minimal detection adjustments

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Minneapolis, MN, United States of America

Nicholas Lojewski