Face Clustering for Dynamic Video Ad Targeting
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Solution Overview
Problem
Existing targeted advertisement systems for linear television struggle to identify users without prior knowledge, making it difficult to provide personalized ads to unknown or new users, and they are not adaptable to changes in user appearances over time.
Innovation Solution
A method and apparatus that uses face clustering for time-varying video to detect and measure users' faces, cluster them, and target advertisements based on these clusters rather than individual users, allowing for dynamic updates and new user integration without requiring prior knowledge of the number of users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If face recognition is used to identify users for targeted advertising, then advertisement personalization is improved, but the system requires prior knowledge of the number of users which limits adaptability to new users
Solution Approach 1:
The patent implements dynamic user identification by continuously capturing facial images and adapting the user database in real-time. Instead of requiring predetermined user registration, the system dynamically adds new users as they appear, removing the need for fixed user knowledge while maintaining personalized advertising capability
Solution Approach 2:
The system performs automatic user identification and database updates without requiring manual user registration or system configuration. The facial recognition system automatically captures, processes, and stores new user data, enabling the system to serve itself in adapting to new users while reducing operational complexity
2Adaptability or versatility
If traditional user identification methods are used, then the system structure is simple, but it cannot provide targeted advertisements to unknown or new users
Solution Approach 1:
The patent replaces traditional manual user registration and identification methods with automated facial recognition technology. This substitution enables the system to automatically identify and adapt to unknown users without complex manual processes, achieving both enhanced adaptability and manageable system complexity through automated optical recognition
3Measurement precision
If the system stores detailed facial data for each user, then advertisement targeting precision is improved, but data storage requirements and processing complexity increase
Solution Approach 1:
The patent extracts only the essential facial features necessary for identification and clustering, rather than storing complete facial images or excessive data. By selecting and storing only critical biometric parameters, the system achieves high identification precision while minimizing data storage requirements and processing complexity
Data Source
AI summary
A method and apparatus for providing targeted advertisements is provided herein. In particular, targeted advertisements are provided to users based on face clustering for time-varying video. During operation video is continuously obtained of users of the system. Users' faces are detected and measured. Measurements of users' faces are then clustered. Once the clusters are available, advertisements are targeted at clusters rather than individual users.