Mobile Product Recognition via Image Matching and Server Offloading
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Solution Overview
Problem
Retailers face challenges in enhancing customer engagement and convenience in product selection and purchase through mobile computing devices, as existing methods lack efficient and user-friendly solutions for identifying and acquiring products using image recognition technology.
Innovation Solution
A product recognition system utilizing computer image recognition techniques on mobile devices, which captures product images, compares them to a database, and provides information such as price, availability, and reviews, allowing users to add products to lists or purchase directly through an e-commerce interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional product identification methods are used in retail, then customers can locate products, but the process is time-consuming and lacks convenience
Solution Approach 1:
The patent replaces manual product search and identification methods with an automated image recognition system. The camera captures product images, and computer vision algorithms automatically identify products, substituting the mechanical process of manually searching shelves and reading labels with an automated visual recognition system that provides instant product identification.
Solution Approach 2:
The system enables customers to independently identify and select products using their mobile devices without requiring assistance from store staff or manual consultation of product catalogs. The image recognition system processes customer-captured images and automatically provides product information, making the entire product identification process self-service oriented.
2Reliability
If retailers implement comprehensive product tracking and customer engagement systems, then customer service quality improves, but system complexity increases
Solution Approach 1:
The mobile device functions as a multi-purpose tool that combines camera, image recognition processing, product database access, and e-commerce transaction capabilities into a single system. This universal device performs multiple functions (product identification, information retrieval, comparison, and purchase) without requiring separate specialized systems for each function, thereby improving service quality while managing system complexity.
Solution Approach 2:
The patent introduces a server as an intermediary that handles complex tasks such as storing product databases, processing image recognition results, and managing e-commerce transactions. This intermediary server absorbs system complexity, allowing the customer's mobile device to remain relatively simple while still providing comprehensive product identification and purchase capabilities.
3Productivity
If image recognition technology is implemented for product identification, then product selection efficiency increases, but computational requirements and processing time may increase
Solution Approach 1:
The image recognition process is segmented into distinct stages: image capture by the camera, preliminary processing and feature extraction on the mobile device, transmission of extracted features to the server, and final product identification and information retrieval. This segmentation allows computationally intensive tasks to be distributed, with the mobile device handling only lightweight preprocessing and the server handling complex matching operations, thereby maintaining high efficiency while managing processing time.
Solution Approach 2:
The system performs preliminary actions by pre-processing the captured image on the mobile device before transmission, including extracting key visual features and reducing image dimensions. This preliminary processing reduces the computational burden on the server and accelerates the overall identification process, as the server receives pre-processed data rather than raw images, thereby improving productivity while minimizing additional processing time.
Data Source
AI summary
A system for computer-aided visual recognition of products may be used by a customer operating a mobile computing device having a camera. A customer can direct the camera at a targeted product for which the customer desires to purchase or learn information. Image recognition operations can be carried out to compare the captured image against images from a prepopulated product image store of known products. Upon a positive match, information regarding the identified product may be gathered and transmitted to the customer and displayed on the mobile computing device. The customer may be presented with various options regarding the identified product, including adding the product to a shopping list, a to-do list, a wish list, or other types of lists.