Image Generation System Error-Tolerant Face Position Detection
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Solution Overview
Problem
Existing image generation systems face challenges in accurately generating face images due to errors in detecting face position and feature points, leading to inconsistencies and reduced accuracy in image normalization and perturbation.
Innovation Solution
An image generation system that includes a detection unit for identifying face position and feature points, an acquisition unit that accounts for detection errors by generating perturbed position information, and a generation unit that creates new images based on this perturbed information, allowing for improved image normalization and perturbation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If face position and feature points are detected from images, then image generation can proceed, but detection errors reduce the accuracy and consistency of generated images
Solution Approach 1:
The system performs preliminary actions by detecting multiple candidate positions and feature points before final image generation. The detection unit identifies several possible face positions and feature points, and the selection unit chooses the most appropriate ones based on predetermined criteria, ensuring accurate and consistent image generation despite detection errors in individual measurements
Solution Approach 2:
The system implements feedback mechanisms where the detection unit continuously monitors and detects face positions and feature points, the evaluation unit assesses the quality and consistency of detected features, and the selection unit adjusts its choices based on this feedback. This closed-loop approach improves both detection accuracy and image generation reliability by learning from detection errors and adjusting accordingly
2Reliability
If multiple position information are detected to account for errors, then image generation robustness improves, but system complexity increases
Solution Approach 1:
The system segments the complex task of handling detection errors into distinct functional units: a detection unit that identifies multiple candidate positions, a selection unit that chooses appropriate positions based on predetermined criteria, and an image generation unit that creates images. This segmentation manages complexity by dividing the system into specialized components, each handling a specific aspect of error tolerance
Solution Approach 2:
The detection unit serves multiple functions by detecting both face positions and feature points simultaneously. The selection unit universally applies predetermined criteria to select from multiple candidate positions regardless of the specific image characteristics. This multi-functionality reduces overall system complexity while maintaining robustness against detection errors
Data Source
AI summary
An image generation system includes: a detection unit that detects a position information about a position of a face or a position of a feature point of the face from an image; an acquisition unit that obtains a perturbed position information that takes into account an error that occurs when the position information is detected, for the position information; and a generation unit that generates a new image including the face on the basis of the perturbed position information. According to such an image generation system, it is possible to properly generate a new image in view of the error in position estimation.