Multi-Camera Auto Exposure Using Map-Based ROI Control
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Solution Overview
Problem
Conventional image processing systems face challenges with overexposure and underexposure issues, particularly in autonomous vehicles, where sudden changes in light exposure can render the point of focus unviewable due to the entire image being affected, rather than just the region of interest.
Innovation Solution
A computer-implemented method that determines a localization parameter of an autonomous vehicle, identifies a region of interest, and adjusts the exposure setting of its cameras based on this information, using sensors like LiDAR and cameras to minimize exposure issues and maintain visibility of critical regions such as traffic signs and pedestrians.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If conventional exposure algorithms adjust exposure settings based on the entire image, then the overall image quality is improved, but the region of interest may become unviewable due to overexposure or underexposure
Solution Approach 1:
The patent segments the image into multiple regions including a region of interest (ROI) and other areas. Different exposure settings are applied to different regions, allowing the ROI to maintain proper visibility while other areas are exposed according to their local lighting conditions. This resolves the contradiction by preventing the entire image from being uniformly adjusted, thus preserving ROI visibility.
Solution Approach 2:
The patent implements local quality control by determining exposure settings specifically for the region of interest based on its local lighting conditions, rather than applying a global exposure setting to the entire image. This allows the ROI to have optimized exposure while other areas are handled separately, resolving the contradiction between overall image quality and ROI visibility.
2Illumination intensity
If the exposure setting is adjusted to compensate for the entire viewing screen, then the overall image brightness is improved, but the point of focus becomes unviewable due to overexposure or underexposure
Solution Approach 1:
The patent divides the image into a point of focus region and other regions, applying separate exposure control to each. The point of focus maintains its visibility by having its exposure setting determined independently based on local conditions, while other areas are adjusted for overall brightness. This resolves the contradiction between image brightness and point of focus visibility.
Solution Approach 2:
The patent applies local quality control by determining exposure settings specifically for the point of focus based on its local lighting conditions, rather than applying a uniform global exposure setting. This allows the point of focus to maintain proper visibility while other areas are optimized for overall brightness, resolving the contradiction between image brightness and measurement precision of the point of focus.
3Measurement precision
If users manually identify the point of focus and determine exposure compensation, then the exposure accuracy for the region of interest is improved, but the system complexity and user burden increase
Solution Approach 1:
The patent implements self-service by automatically identifying the region of interest and determining its exposure setting without requiring manual user input. The system uses sensors and image processing to autonomously detect the ROI and calculate appropriate exposure parameters, resolving the contradiction by maintaining high exposure accuracy while eliminating user burden and reducing system complexity.
Solution Approach 2:
The patent uses feedback mechanisms where sensors continuously monitor lighting conditions in the region of interest, and the system automatically adjusts exposure settings based on this feedback. This closed-loop control maintains high exposure accuracy while automating the process, eliminating the need for manual user intervention and reducing system complexity.
Data Source
AI summary
The subject disclosure relates to techniques for adjusting an exposure setting. A process of the disclosed technology can include steps for determining a localization parameter of an autonomous vehicle, the localization parameter including a geographic position of the autonomous vehicle, determining a region of interest based on the localization parameter of the autonomous vehicle, receiving a first image including the region of interest based on the localization parameter of the autonomous vehicle, determining an exposure setting for the region of interest in the first image, and adjusting an exposure setting of the first image to the exposure setting for the region of interest in the first image. Systems and machine-readable media are also provided.