Personalized Camera Calibration for Darker Skin Tones
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Solution Overview
Problem
Current cameras are not designed to account for and optimize pictures and videos for all skin tones, particularly in varying lighting conditions, leading to inadequate image capture for users with darker skin tones.
Innovation Solution
A camera personalization interface is displayed on a client device to receive setting selections based on a user's skin tone or undertone, with pre-capture and post-processing settings determined and applied to ensure high-quality image capture and modification for all users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If cameras are designed to capture lightened parts or focus on brightness, then image capture works well in bright lighting conditions, but image quality deteriorates for users with darker skin tones in low light conditions
Solution Approach 1:
The camera system changes its operational parameters by detecting skin tone characteristics and adjusting exposure, white balance, and dynamic range settings accordingly. The system monitors lighting conditions and skin tone data to modify capture parameters in real-time, ensuring optimal image quality across different skin tones and lighting scenarios.
Solution Approach 2:
The camera employs dynamic adjustment mechanisms that continuously adapt to changing lighting conditions and skin tone characteristics. The system dynamically modifies exposure settings, focus parameters, and processing algorithms based on real-time detection of skin tone and environmental lighting, enabling consistent performance across diverse conditions.
2Ease of operation
If cameras search for lightened parts to calibrate themselves, then calibration works in bright conditions, but the camera becomes inactive or produces poor images when no lightened part is present
Solution Approach 1:
The camera system performs self-calibration by detecting skin tone characteristics and automatically adjusting its parameters without requiring external reference objects or manual intervention. The system uses the subject's skin tone as the calibration reference, enabling automatic adaptation to different lighting conditions and skin tones.
Solution Approach 2:
The camera performs preliminary detection of skin tone and lighting conditions before capturing the image. By pre-calibrating based on detected skin tone characteristics and environmental lighting, the system prepares optimal capture settings in advance, ensuring reliable operation even when no lightened parts are present in the scene.
3Difficulty of detecting and measuring
If facial tracking technology is used to recognize faces, then face detection works in well-lit conditions, but darker skin tones cannot be recognized in some lighting conditions
Solution Approach 1:
The facial tracking system adjusts its detection parameters by monitoring skin tone characteristics and lighting conditions. The system modifies contrast thresholds, color sensitivity ranges, and feature detection algorithms based on detected skin tone data, enabling reliable face recognition across diverse skin tones and lighting scenarios.
Data Source
AI summary
Method of generating modified media content item based on user's setting selection starts with a processor causing a camera personalization interface to be displayed by a display of a client device. The processor receives a setting selection from the client device via the camera personalization interface. The processor determines a pre-capture setting and a post-processing setting based on the setting selection. The processor calibrates a camera of the client device using the pre-capture setting. The processor receives a media content item including an image captured using the camera and generates a modified media content item by modifying the media content item using the post-processing setting. Other embodiments are described herein.