Retail Gesture Recognition Using Machine-Readable Images
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Solution Overview
Problem
Current retail processes in environments like grocery stores lack efficient methods for user interaction with products, particularly in facilitating purchases and inventory management using machine-readable images and user gestures.
Innovation Solution
A system utilizing a computing device with an image capture device and retail process manager to capture and interpret machine-readable images and user gestures, enabling augmented reality interfaces for tasks such as product identification, inventory management, and purchase transactions through gestures like pointing and swiping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual product identification and inventory methods are used, then operational simplicity is maintained, but productivity and measurement precision are reduced
Solution Approach 1:
The patent replaces manual mechanical scanning methods with an automated image capture and processing system. The computing device captures images of machine-readable images (barcodes, QR codes) and automatically processes them to identify products, replacing the need for manual scanning operations and improving productivity while managing system complexity through software-based solutions.
Solution Approach 2:
The system enables self-service product identification and inventory management. Customers can independently scan products using their computing devices, and the system automatically processes the information without requiring manual intervention from store personnel, thereby improving productivity while keeping the system relatively simple to deploy.
2Loss of time
If manual inventory management is used, then ease of operation is maintained, but loss of time and productivity increase
Solution Approach 1:
The system enables continuous inventory management by capturing images of machine-readable images in real-time as products are placed or removed from shelves. The computing device continuously processes these images to update inventory status, eliminating the need for periodic manual counting and significantly reducing time loss while maintaining ease of operation through automated processes.
Solution Approach 2:
The system performs preliminary identification and categorization of products as they are placed on shelves. By capturing and processing images of machine-readable images immediately when products arrive, the system prepares inventory data in advance, reducing the time required for subsequent inventory management tasks while keeping operations simple and automated.
3Productivity
If traditional purchase processes are used, then device complexity is minimized, but loss of time and productivity are reduced
Solution Approach 1:
The patent replaces traditional manual checkout processes with automated image recognition and processing. The computing device captures images of machine-readable images on products, automatically identifies them, and processes purchase transactions without requiring manual scanning or data entry, significantly improving transaction efficiency while reducing the time loss associated with traditional checkout procedures.
Data Source
AI summary
Systems and methods for implementing retail processes based on machine-readable images and user gestures are disclosed. According to an aspect, a method includes capturing one or more images including a machine-readable image and a user hand gesture. The method also includes identifying the machine-readable image as being associated with a product. Further, the method includes determining whether the user hand gesture interacts with the machine-readable image in accordance with a predetermined gesture. The method also includes implementing a predetermined retail process in association with the product in response to determining that the user hand gesture interacts with the machine-readable image in accordance with the predetermined gesture.