Eye State Image Synthesis for Better Group Photo Quality
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Solution Overview
Problem
Capturing group photos often requires repeated re-shooting due to unideal eye states, leading to reduced user satisfaction with the final image quality.
Innovation Solution
An image processing method that performs eye state detection on a set of captured images to identify and synthesize target effect images with ideal eye states, improving the eye state effect and overall image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If repeated re-capturing is performed to achieve ideal eye state, then image quality is improved, but user experience and time efficiency deteriorate
Solution Approach 1:
The system performs eye state detection on multiple captured images in advance to identify images with ideal eye states before the user needs to select the final photo. This preliminary screening allows the system to prepare suitable images ahead of time, eliminating the need for repeated re-capturing and improving both image quality and time efficiency.
Solution Approach 2:
The system provides feedback by automatically selecting and presenting images with ideal eye states to the user, allowing them to review and confirm the final photo without needing to re-capture. This feedback mechanism ensures that the selected image meets the quality requirement while saving time by avoiding unnecessary re-shooting.
2Ease of operation
If manual selection from multiple photos is performed, then user control is improved, but user convenience and satisfaction deteriorate
Solution Approach 1:
The system performs self-service by automatically detecting eye states and selecting the most suitable image without requiring manual intervention. The system independently evaluates multiple captured images, identifies those with ideal eye states, and presents them for final confirmation, thereby simplifying the user's task while maintaining control over the final selection.
3Manufacturing precision
If eye state detection is performed on all captured images, then image quality is improved, but processing time and computational resources deteriorate
Solution Approach 1:
The system segments the image processing task by detecting eye states only on images that meet basic capture criteria, rather than analyzing all captured images uniformly. This segmentation approach allows the system to focus computational resources on the most relevant images, improving quality assessment while reducing overall processing time and resource consumption.
Data Source
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AI summary
The present disclosure provides an eye state detection-based image processing method and apparatus, a device, and a storage medium. The method comprises: detecting eye states of a target face in an image set to be processed to obtain target area images in which the eye states meet a preset condition, then determining therefrom a target effect image corresponding to the target face, and finally synthesizing the target effect image onto a reference image in the image set to be processed to obtain a target image corresponding to the image set to be processed. In the present disclosure, a target effect image for each face is determined on the basis of eye state detection, and then each target effect image is synthesized onto a reference image, so that the effect of the eye state of each face in a target image can be improved, the quality of the target image is ensured, and the satisfaction of a user for the target image is improved.