Walmart Apollo, LLC

Han Zhang

Lingfeng Zhang

Zhaoliang Duan

Avinash Madhusudanrao Jade

Raghava Balusu

Mingquan Yuan

Wei Wang

Zhichun Xiao

Tianyi Mao

William Craig Robinson

Amit Jhunjhunwala

Benjamin R Ellison

Srinivas Muktevi

Ashlin Ghosh

Abhinav Pachauri

Paul Lewis Lobo

Jing Wang

Feiyun Zhu

Haining Liu

Pingjian Yu

Yao Liu

Jon Hammer

Yutao Tang

Sicong Fang

Joseph Duffy

Chunmei Wang

Muzzammil Afroz

Yu Tao

Pingyuan Wang

Zhiwei Huang

Xiang Yao

Michael Alvin Schubert, Jr

Huanyu Zang

Vincent St Jon Cucco

Examples provide an archway truss for supporting devices, such as sensor devices generating sensor data for objects passing through the archway and a digital display device displaying dynamic content to users moving through the archway. The archway truss includes vertical support members attached to a horizontal top member. A central support member is reinforced to protect against cart impacts. Cameras are attached to the archway truss and positioned to capture images of objects in carts moving through the archway truss. Radio frequency identification (RFID) tag readers and other sensor devices are removably attached to the archway truss to gather item identification data for objects in the carts. Pairs of wing barriers are provided for each vertical support to block the field of view of the cameras from objects outside the lanes formed by the archway truss. An exterior covering provides padding to protect users contacting the archway truss.

Archway truss device with interactive exit lanes

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 detect one or more adjacent product storage structures (shelves, pallets, etc.) and identifies and selects a single image that fully shows a product storage structure of interest and fully shows each of the products stored on the product storage structure of interest.

Systems and methods of selecting an image from a group of images of a retail product storage area

Systems and methods of verifying pairings of price tag labels and products at a product storage facility include an image capture device that moves about and captures images of product storage structures at the product storage facility, and a database that stores inventory data associated with the products stocked at the product storage facility. A computing device processes the images to extract one or more characters from the price tag labels and products detected in the images, correlates the extracted characters to the inventory data to identify a product code and a product name that matches the characters extracted from the price tag labels and the products. If the characters extracted from the price tag and from the on-shelf product to which the price tag label is allocated match, the database is updated to reflect that the price tag label is properly allocated to the appropriate on-shelf product.

Systems and methods of verifying price tag label-product pairings

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. The computing device obtains the keyword and feature model templates associated with a recognized product from the electronic database, extracts the keywords from the products associated with the obtained keyword model templates, identifies products that are similar to the recognized product, and updates the keyword model template for each of the products to include must keywords and negative keywords, facilitating recognition of products in subsequent images captured by the image capture device.

Systems and methods of updating model templates associated with images of retail products at product storage facilities

Systems and methods of analyzing on-shelf price tag labels and products at a product storage facility include an image capture device that captures one or more images of one or more product storage structures at a product storage facility. A computing device communicatively coupled to the image capture device analyzes the images of the product storage structures captured by the image capture device and detects individual price tag labels and individual products located on the product storage structure. Based on the detection of the price tag labels and the products, the computing device also defines separate product storage spaces of the product storage structure, determines which price tag labels are allocated to which of the separate product storage spaces, and associates in a database the price tag labels allocated to the product storage spaces with the products stored in those product storage spaces.

Systems and methods of detecting price tags and associating the price tags with products

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.

Systems and methods of identifying individual retail products in a product storage area based on an image of the product storage area

A transaction record is created showing a purchase transaction of a customer. A CV profile showing a list of items in the transaction obtained from images is also obtained. The items in the transaction record are compared to items on the list. When there is a discrepancy, an action to take is determined.

System and method for detecting unpaid items in retail store transactions

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Allen, TX, United States of America

Han Zhang