Digital Signage Personalization via User Image Analysis
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Solution Overview
Problem
Existing digital signage systems for e-commerce lack the ability to provide personalized product recommendations to users due to the absence of viewer profiles, resulting in low user engagement and limited conversion rates.
Innovation Solution
A system that captures user images using a camera, processes them to determine features such as age, gender, and dressing style, and recommends products based on these characteristics, allowing users to select items without touching the screen and engaging them with interactive games and coupons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static advertisements are shown on public boards, then the system is simple and low-cost, but user engagement is low and the advertisements are only interesting to a small population
Solution Approach 1:
The patent transforms static advertisement boards into dynamic digital signage systems that can display different advertisements based on real-time user characteristics. The system uses cameras to capture user images, processes these images to determine features like age, gender, and dressing style, and then dynamically selects and displays personalized advertisements, making the system adaptable to different users while maintaining operational simplicity
Solution Approach 2:
The system changes the parameters of the advertisement content based on user parameters extracted from images. By analyzing user features (age, gender, dressing style) and matching them with product databases, the system dynamically adjusts which advertisements are displayed, transforming a fixed-content system into a variable-content system that adapts to user characteristics
2Adaptability or versatility
If digital signage displays many dynamic advertisements, then the system is more interesting for broader viewers, but the system cannot provide personalized recommendations due to lack of viewer profiles
Solution Approach 1:
The system performs preliminary actions by capturing and processing user images before displaying advertisements. It extracts relevant features from user images (age, gender, dressing style) and uses these pre-analyzed characteristics to select personalized advertisements, eliminating the need for separate profile creation while enabling personalization
Solution Approach 2:
The patent introduces an intermediary process between the user and the advertisement display. Instead of requiring direct user input or profile data, the system uses image processing as an intermediary to indirectly obtain user characteristics and match them with appropriate products, bridging the gap between anonymous users and personalized content
3Adaptability or versatility
If the system captures and processes user images to determine features, then personalized recommendations can be provided, but the device complexity and processing requirements increase
Solution Approach 1:
The patent segments the image processing task into distinct functional modules: image capture by camera, feature extraction (age, gender, dressing style), product database matching, and advertisement selection. This modular segmentation allows each component to be optimized independently and simplifies the overall system architecture while maintaining comprehensive personalization capabilities
Data Source
AI summary
Method and system for electronic commerce are provided. An image of a user is obtained. A plurality of features based on the image of the user is determined. A group of products based on the plurality of features are selected. A recommendation to the user is provided based on the group of products.