Synthetic Face Dataset Generation via Parameter Manipulation
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Solution Overview
Problem
Existing face image datasets for AI model learning face challenges in protecting privacy and ensuring fairness, particularly due to ethical risks associated with using real face image data and the high construction costs involved.
Innovation Solution
A data creation method that involves converting source images of freely-selected faces into numerical creation parameters, which are then partially or wholly changed to generate a larger number of input creation parameters. These parameters are used to create face image data items, resulting in a face image dataset that includes only imaginary faces, thus ensuring privacy protection and fairness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If real face image data is collected from websites or actual measurement to construct face image datasets, then the dataset can be obtained, but privacy protection is compromised and ethical risks increase
Solution Approach 1:
The patent creates synthetic face images that copy the statistical properties and visual characteristics of real faces without using actual personal data. By generating artificial face images through parameter-based synthesis, the system produces dataset copies that maintain utility for AI training while eliminating privacy risks associated with real individual data.
Solution Approach 2:
The patent employs inexpensive source images freely selected from available images, converting them into synthetic face data through parameter manipulation. This approach replaces expensive and ethically problematic real face data collection with a disposable, cost-effective synthesis method that does not require ongoing consent or privacy management.
2Quantity of substance
If only real face images are used to construct face image datasets, then the dataset can be created, but construction cost increases and fairness is difficult to ensure
Solution Approach 1:
The patent systematically manipulates creation parameters including age, gender, ethnicity, and facial features to generate diverse synthetic face images. By changing these parameters across multiple source images, the system efficiently produces a fair and balanced dataset without the high costs associated with collecting and curating real face images from diverse populations.
Solution Approach 2:
The patent creates a multi-functional system that can generate face images across various demographics and attributes from a single synthesis framework. This universal approach allows one system to produce datasets suitable for multiple AI training scenarios, eliminating the need for separate expensive data collection campaigns for each demographic group.
3Adaptability or versatility
If real face images are collected to ensure diverse attributes such as age and gender, then fairness can be improved, but collection difficulty and cost increase significantly
Solution Approach 1:
The patent directly controls creation parameters to achieve desired attribute distributions. By adjusting parameters such as age, gender, and ethnicity during the synthesis process, the system ensures attribute diversity and fairness without the logistical challenges of collecting and verifying real face images from diverse sources.
Solution Approach 2:
The patent incorporates feedback mechanisms that evaluate the statistical properties of generated face images and adjust parameter distributions accordingly. This feedback loop ensures that the synthetic dataset achieves target fairness metrics for attributes like age and gender, automatically correcting imbalances without manual data collection and curation efforts.
Data Source
AI summary
The present technology relates to a data creation device, a data creation method, and a program by which a face image dataset suitable for AI model learning can be obtained.The data creation device creates, by partially or wholly changing a creation parameter which is obtained by conversion of a source image of a freely-selected face to a numerical value, a larger number of input creation parameters than a predetermined number from the predetermined number of the creation parameters of the source images, and creates, by creating a face image data item on the basis of a plurality of the input creation parameters, a face image dataset including a plurality of the face image data items. The present technology is applicable to a data creation device.