Driver Assistance Camera Optics for ROI Pixel Concentration
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Solution Overview
Problem
Conventional camera-based driver assistance systems suffer from inefficient pixel distribution, leading to suboptimal use of sensor resources and increased costs due to uniform pixel density across the field of view, while lens distortion is traditionally corrected rather than exploited for enhancing pixel density in regions of interest.
Innovation Solution
Utilizing Global Shutter (GS) cameras with intentionally engineered lens distortions to increase pixel density in regions of interest (ROIs) through controlled distortion compensation, allowing for higher system accuracy and reliable detection of obstacles and driver parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If uniform pixel density is used across the field of view, then the camera captures the entire area evenly, but sensor resources are used inefficiently and costs increase
Solution Approach 1:
The patent applies local quality by creating non-uniform pixel density distribution where regions of interest (such as the driver's face, hands, or road areas) have higher pixel density while other areas have lower pixel density. This is achieved through optical lens design or image processing that concentrates sensor resources in critical areas, improving measurement precision where needed while reducing waste in less important areas.
2Shape
If lens distortion is corrected traditionally, then the image appears geometrically accurate, but pixel density in regions of interest is reduced
Solution Approach 1:
The patent inverts the traditional approach by intentionally introducing or retaining lens distortion rather than correcting it. This distortion is designed to increase pixel density in regions of interest. The system accepts geometric distortion as a trade-off to achieve higher pixel density and improved measurement precision in critical areas, effectively doing the opposite of conventional distortion correction.
3Measurement precision
If higher pixel density is concentrated in regions of interest, then detection accuracy improves, but the field of view coverage becomes uneven
Solution Approach 1:
The patent applies local quality by creating non-uniform pixel density distribution where regions of interest (such as the driver's face, hands, or road areas) have higher pixel density while other areas have lower pixel density. This is achieved through optical lens design or image processing that concentrates sensor resources in critical areas, improving measurement precision where needed while reducing waste in less important areas.
Data Source
AI summary
A driver assistance system for a vehicle, the driver assistance system comprising a camera mounted on the vehicle and configured to capture one or more images inside and/or outside of the vehicle, and a processing unit, wherein the camera has a defined field of view (FOV), the camera comprises an optical lens that causes a distortion of the captured images, the processing unit is configured to perform distortion compensation on the images captured by the camera, wherein a pixel density in the resulting compensated images is increased in defined areas of the image due to the distortion, and the defined areas of increased pixel density in the compensated images correspond to a region of interest (ROI) within the image, wherein the ROI is smaller than the FOV of the camera.