Facial Feature Matching for Ad-to-Purchase Effectiveness Tracking
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Solution Overview
Problem
Existing technologies struggle to analyze the relationship between advertisement viewers and their subsequent purchases when the advertisement display and imaging device are separate, necessitating a built-in camera or an external camera interface.
Innovation Solution
An information processing system that uses external imaging devices to capture facial features of viewers and purchasers, compares these features to identify matching individuals, and determines the effectiveness of advertisements by linking advertisement viewing with purchase data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a built-in camera is integrated into the advertisement display device, then the device can directly capture viewer images and associate them with advertisement data, but the device structure becomes more complex and costly
Solution Approach 1:
The system separates the imaging function from the advertisement display device. External imaging devices (cameras) are positioned independently to capture viewer images, while the advertisement display device focuses on displaying ads. The server integrates data from both sources, achieving functional segmentation that simplifies individual device structures while maintaining overall system capability.
Solution Approach 2:
The server acts as an intermediary that collects data from both the advertisement display device and external imaging devices. It receives advertisement viewing data from the display device and image data from external cameras, then processes and associates this data to determine advertisement effectiveness, eliminating the need for built-in cameras in the display device.
2Adaptability or versatility
If an external camera interface is provided in the advertisement display device, then the device can connect to external imaging devices, but the device complexity increases due to additional interfaces and connection requirements
Solution Approach 1:
The server provides universal data collection capabilities by receiving data from multiple sources including the advertisement display device and various external imaging devices through standard communication protocols. This multi-functional approach allows the system to work with different imaging devices without requiring specialized interfaces in the advertisement display device itself.
3Device complexity
If separate external imaging devices are used instead of built-in cameras, then the advertisement display device structure is simplified, but it becomes difficult to associate viewer images with advertisement viewing data
Solution Approach 1:
The server establishes a feedback mechanism that collects advertisement viewing data from the display device and image data from external cameras, then processes this feedback information to associate viewers with viewed advertisements. This closed-loop data collection and processing ensures that even with separate devices, the system can effectively link viewer images with advertisement viewing events.
Data Source
AI summary
A face image of a customer A viewing an advertisement displayed on an advertisement display is captured by a camera, and a facial feature amount is acquired from the captured face image in a terminal device. A face image of a customer B purchased a commodity at a POS terminal is captured by a camera, and a facial feature amount is acquired from the captured face image in a terminal device. When it is determined that these customers are the same person based on comparison result of the facial feature amounts, the commodity viewed on the advertisement display and the commodity purchased at the POS terminal are specified. Then, it is determined whether these commodities are the same commodity. If the commodities are the same commodity, it is determined that the advertisement display is effective.