Color-Calibrated Product Imaging for Accurate Virtual Try-On
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Solution Overview
Problem
Existing methods for matching personal care products to consumers are inaccurate due to manufacturing variations and environmental lighting conditions, and virtual try-on applications fail to account for actual product characteristics.
Innovation Solution
A system that encodes personal care products with QR codes containing color calibration targets, allowing consumers to capture images that are adjusted for lighting conditions, and sends data to a backend system for accurate product recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual inspection of the product is used to determine color accuracy, then the consumer can see the actual product, but the view is highly dependent on lighting and environmental conditions resulting in inaccurate color perception
Solution Approach 1:
A color calibration target with known color values is introduced as an intermediary reference object in the image. This target serves as a mediator between the lighting conditions and the product color measurement, allowing the system to calculate correction parameters that compensate for lighting effects and achieve accurate color representation.
Solution Approach 2:
The system captures the color calibration target along with the product, analyzes the actual color values of the target under current lighting conditions, and uses this feedback to determine correction parameters. These parameters are then applied to adjust the product image colors, creating a closed-loop feedback system that achieves accurate color measurement despite varying lighting conditions.
2Ease of operation
If virtual try-on applications use intended product color rather than actual product color, then the application can provide virtual try-on experience, but the color does not match the actual product characteristics due to manufacturing variations
Solution Approach 1:
The color calibration target is placed on the actual product batch during manufacturing or quality control, and its color values are captured and stored in advance. This preliminary action creates a reference database of actual product colors that can be used later for accurate virtual try-on applications, eliminating the need to rely on intended color specifications.
Solution Approach 2:
Instead of using the intended product color specification, the system creates a digital copy of the actual product color by capturing images of the color calibration target placed on the actual product batch. This digital copy accurately represents the real product characteristics including manufacturing variations, enabling precise virtual try-on that matches the actual product.
3Extent of automation
If color calibration target with machine-readable information is used, then automated color measurement and product identification can be achieved, but the system complexity increases
Solution Approach 1:
The color calibration target is merged with a machine-readable code (such as QR code) into a single integrated component. This combination allows the system to automatically identify the product and retrieve associated color information from the machine-readable code, then use the color calibration target for automated color measurement, reducing the need for separate manual operations.
Solution Approach 2:
The color calibration target is designed to serve multiple functions: it provides color reference for calibration, contains machine-readable information for product identification, and can be automatically recognized by image processing algorithms. This multi-functionality reduces system complexity by eliminating the need for separate components for each function.
Data Source
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AI summary
A computing device obtains a digital image of a color calibration target for a product; obtains product information for the product; determines image adjustment information based on the digital image of the color calibration target; obtains a digital image of the product based on the image adjustment information; and transmits the image data of the product and the product information to a backend product computer system. Obtaining the product information for the product may include scanning a graphical code, such as a QR code or a bar code, or obtaining information from the product via short-range radio-frequency communication. The method may further include receiving a response from the backend product computer system, which may include additional product information. The color calibration target and encoded product information may be included in a QR code having three or more color regions.