Edge Device Audiovisual Content Analysis with Compressed ML Models
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Solution Overview
Problem
Current systems lack efficient methods to accurately detect and extract advertised products from audiovisual content in real-time streaming, limiting user interaction and commerce opportunities.
Innovation Solution
The implementation of a content detection engine using trained machine learning models, such as CNNs, combined with model weight compression techniques, enables the analysis of audiovisual frames to identify products and provide actionable information to users, facilitating seamless integration with streaming commerce engines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If trained machine learning models are used to detect and extract advertised products from audiovisual content in real-time streaming, then measurement precision and productivity are improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary component (content detection engine with trained machine learning models) that mediates between the audiovisual content stream and the user interface. This intermediary performs the complex detection and extraction tasks, allowing the main streaming system to maintain its simplicity while achieving high measurement precision in product detection.
2Productivity
If real-time analysis of audiovisual frames is performed to identify products, then productivity is improved, but use of energy increases
Solution Approach 1:
The system performs partial analysis by focusing computational resources only on frames that contain potential product advertisements rather than analyzing every frame in the stream. This selective approach maintains real-time productivity while significantly reducing overall energy consumption compared to exhaustive frame-by-frame analysis.
3Adaptability or versatility
If user interaction with identified products is enabled through user interfaces, then adaptability is improved, but device complexity increases
Solution Approach 1:
The user interface component is designed with multi-functionality, serving both as a display mechanism for streaming content and as an interaction platform for product engagement. This universal design allows the same interface to handle both content delivery and commerce operations, improving adaptability without proportionally increasing device complexity.
Data Source
AI summary
Techniques for analyzing audiovisual content, such as streaming content are disclosed. In one embodiment, a method is disclosed comprising obtaining a frame of audiovisual content, using a video decoder to decode compressed model weights of at least one trained model, using the at least one trained model with the decoded weights to analyze the frame and extract content based on the analysis, using the extracted content to make a determination that the audiovisual content comprises a category of content, and causing actionable information to be transmitted to a client device of a user in response to the determination that the audiovisual content comprises the category of content.