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🎧 Listen and Explore 🗺️ the engaging audio discussion about the innovative patent “SYSTEM AND METHOD FOR PROVIDING ADVERTISEMENT CONTENTS BASED ON FACIAL ANALYSIS WO2020141969A2”!

This system leverages facial recognition technology to deliver personalized, dynamic ads tailored to users based on age, gender, emotions, and more—while prioritizing privacy! 🔒✨ Discover how AI is revolutionizing digital advertising by matching ads to user profiles without the need for direct personal data collection.

🔗 Mindmap visualization available too! Uncover how this innovation is shaping the future of advertising. #AI #FacialRecognition #DigitalMarketing #Innovation #LLM

SYSTEM AND METHOD FOR PROVIDING ADVERTISEMENT CONTENTS BASED ON FACIAL ANALYSIS WO2020141969A2

In this text delves into his patented innovation that transforms digital advertising by utilizing facial analysis to deliver targeted content. The system captures images of users through an embedded camera in digital signage and employs advanced face detection and analysis modules to extract key facial features such as age range, gender, emotions (e.g., happy, sad, angry), styles (e.g., eyeglasses, beard), and attention indicators like gaze direction.

By statistically analyzing these features using trained classification models, the system computes a “weighted image” representing the user’s profile. This profile is then matched with a database of weighted advertisements based on predefined matching rules provided by advertisers. The most relevant advertisement is seamlessly displayed on the screen, enhancing user engagement by presenting content tailored to the individual’s possible interests—all without directly collecting personal information.

This innovative approach overcomes the limitations of traditional digital advertising, which often lacks interactivity and personalization. By integrating deep learning technologies and ensuring user privacy, Dr. Pirahansiah’s system offers a dynamic and efficient solution that benefits both advertisers and consumers, marking a significant advancement in the field of digital advertising.

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Patent Application WO 2020/141969 A2 - Digital Advertising System

1. Field of Invention

• Focuses on digital advertising.
• Utilizes facial analysis to provide targeted ad content.
• Enhances user engagement based on demographic and behavior data.

2. Background of the Invention

• Digital advertising has grown in popularity.
• Traditional digital standees provide static and passive content.
• Limitations:
  • Lacks interaction with users.
  • Does not tailor content based on user preferences.
• Prior Solutions:
  • Use of face recognition to provide targeted ads (e.g., CN107248081 and US 7636454).
  • Shortcomings in full engagement and personalization.

3. Summary of Invention

• Objective: Provide dynamic ad content through facial analysis.
• Extract demographic and behavioral data from users indirectly.
• Match ad content to user preferences.
• Involves facial detection, classification, and weighted image computation.

4. Detailed System Components

• Image Acquisition Device: Captures the user’s image.
• Face Detection Module: Detects and processes the user’s face.
• Analysis Module: Analyzes facial features using classification models.
• Database: Stores rules, ads, and user data for matching.
• Display Device: Shows targeted ad content based on user data.

5. Process Overview

1. Capture user image via image acquisition device.
2. Detect user’s face in the image.
3. Analyze facial features statistically.
4. Compute a “weighted image” based on the analysis.
5. Match the weighted image with appropriate ads using stored rules.
6. Display personalized ad content on the digital standee.

6. Matching Rules

• Use binary sequences for user and advertisement matching.
• Match based on:
  • Order of features.
  • Most similar or important features.
  • Nearest similar features.
• Example: Sunglasses promotion targeting male users based on gender.

7. Embodiments

• Single or Group of Users: The system can adapt to one or multiple users.
• Weighted Image in Binary Form: Key facial features like gender, emotion, style, and attention are encoded in binary.

8. Claims

• System Claims:
  • Provides targeted advertising based on facial analysis.
  • Contains components like image acquisition, face detection, analysis, computation, and display modules.
  • Uses classification models to group facial features.
• Method Claims:
  • Describes a step-by-step process for acquiring images, detecting faces, analyzing features, and matching them with ads.

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