AI Product Recognition in Audio-Visual Content for Immediate Purchase
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Solution Overview
Problem
Existing systems fail to seamlessly identify and facilitate the purchase of products or services presented within digital content, particularly in real-time or near-real-time, without requiring manual intervention or extensive user interaction.
Innovation Solution
An automated system that utilizes computer vision, AI, and product recognition processes to identify products within digital content, determines their availability, and enables immediate purchase through various devices and platforms, including smartphones and smart TVs, using QR codes and viewer preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated product identification systems are implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The patent employs computer vision algorithms and AI models as intermediary components between the digital content and the product identification process. These intermediaries automatically detect, recognize, and extract product information from visual content, enabling seamless product identification without manual intervention while managing system complexity through modular architecture.
Solution Approach 2:
The system replaces manual product identification mechanisms with automated computer vision and image recognition technologies. Instead of requiring users to manually search for or input product information, the system automatically captures frames from digital content, processes them through AI models, and identifies products, thereby significantly improving productivity.
2Loss of time
If real-time product identification is implemented, then loss of time is reduced, but use of energy increases
Solution Approach 1:
The system performs preliminary actions by pre-processing video frames, extracting key visual features, and maintaining product databases in advance. This allows the product identification process to occur rapidly when needed, reducing the actual product selection time while managing energy consumption through efficient preprocessing and caching strategies.
Solution Approach 2:
The system implements periodic frame sampling and processing rather than continuous analysis. By selectively processing key frames or segments of digital content at optimized intervals, the system achieves real-time product identification capability while reducing overall energy consumption compared to continuous full-frame analysis.
3Measurement precision
If comprehensive product recognition is implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the product recognition process into multiple specialized modules: frame extraction, image preprocessing, feature detection, product classification, and information retrieval. Each module focuses on a specific aspect of recognition, improving overall accuracy while managing complexity through modular design and specialized processing for each stage.
Solution Approach 2:
The system employs universal AI models and computer vision algorithms that can recognize multiple product types, categories, and formats using the same core technology platform. This multi-functional approach enables comprehensive product recognition across diverse digital content while avoiding the need for separate specialized systems for each product type, thereby improving precision without proportionally increasing complexity.
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.