In-Content Product Recognition for Seamless Viewer Purchasing
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Solution Overview
Problem
Existing systems fail to efficiently enable viewers to quickly identify and purchase products or services presented in digital content, particularly when product placement data is absent or dynamic, and do not account for user preferences or alternative product sourcing.
Innovation Solution
An automated method and system that analyzes digital content to identify products, communicates with recognition servers for product data, and allows viewers to initiate purchases using various input methods, including AI and computer vision, while considering user preferences and offering alternatives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing systems are used to identify products in digital content, then product identification can be achieved, but seamless purchasing is not enabled and user preferences are not accounted for
Solution Approach 1:
The system integrates multiple functions into a single platform: product identification through computer vision, availability checking across multiple retailers, user preference analysis, and seamless purchasing. This multi-functional approach enables the system to handle the entire product discovery-to-purchase workflow while adapting to individual user preferences and account for product availability across different retailers.
Solution Approach 2:
The system acts as an intermediary between digital content, products, retailers, and users. It bridges the gap by analyzing digital content to identify products, checking availability through intermediary retailer connections, and facilitating purchases while considering user preferences. This intermediary role enables seamless purchasing experiences that existing systems cannot provide.
2Measurement precision
If computer vision and AI are used to identify products without embedded data, then product identification accuracy improves, but system complexity increases
Solution Approach 1:
The system replaces traditional mechanical or manual product identification methods with computer vision and AI technologies. Instead of relying on embedded data or manual tagging, the system uses image recognition algorithms to automatically identify products in digital content, achieving high accuracy while managing complexity through software-based solutions.
Solution Approach 2:
The system creates digital representations or copies of products through computer vision analysis. By generating accurate visual copies and descriptions of identified products, the system enables subsequent availability checking and purchasing workflows without requiring physical interaction with the actual products, thereby managing system complexity while maintaining high identification accuracy.
3Adaptability or versatility
If product availability is checked across multiple retailers, then purchasing options increase, but information processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing connections with multiple retailers and maintaining up-to-date product availability information. When a product is identified in digital content, the system can quickly check availability across pre-connected retailers without requiring time-consuming real-time queries, thus providing multiple purchasing options while minimizing information processing time.
Solution Approach 2:
The system implements self-service mechanisms by automatically checking product availability across multiple retailers and presenting options to users without requiring manual intervention. This automated process reduces information processing time while still providing comprehensive purchasing options across different retailers, as the system handles the information gathering and presentation autonomously.
Data Source
AI summary
An automated system/method for identifying and enabling viewer selection/purchase of products or services associated with digital content presented on a display device. Products within the digital content are identified and existing product placement data is ascertained. For products that do not include such data, other methodologies, with the assistance of third-party servers, are employed to assess identity and purchase availability. Viewer input designate products to assess or products can be automatically assessed. Viewers initiate purchase of identified products via the display device or other electronic devices controlled by viewers, such as via viewers' smart phones. Various processes for identifying products include use of AI processing, access to data on third-party servers, crowd sourcing and other methodologies. Various techniques for selecting products for purchases are employed including employing 3D codes (e.g., QR codes) alongside presented products to enable other portable electronic devices to facilitate purchase. Other features are described.