Driver Assistance Camera Distortion Compensation for ROI Detection

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Solution Overview

Problem

Current camera-based driver assistance systems face challenges in reliably detecting obstacles and changes in driver parameters, such as drowsiness, due to image distortion caused by optical lenses, which affects pixel density and information availability within the field of view.

Innovation Solution

A driver assistance system that utilizes a camera with an optical lens causing distortion, where a processing unit performs distortion compensation to increase pixel density in defined areas of the image, aligning these areas with a region of interest smaller than the camera's field of view, thereby enhancing the detection of obstacles and driver parameters.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If distortion compensation is performed on images captured by a camera with an optical lens, then pixel density in defined areas is increased, but processing complexity increases

Engineering Contradiction:
Improvepixel densityVSAvoidprocessing complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies local quality by performing distortion compensation selectively only in defined areas of the image that correspond to the region of interest, rather than processing the entire image. This approach increases pixel density where needed while minimizing processing complexity by avoiding unnecessary computation in areas outside the region of interest.

Inventive Principle:
Principle #3Local quality

2Reliability

If the region of interest is smaller than the field of view, then detection reliability is improved, but information loss increases

Engineering Contradiction:
Improvedetection reliabilityVSAvoidinformation loss
Core Design Contradiction:
ReliabilityVSLoss of information

Solution Approach 1:

The patent focuses processing resources on the region of interest by increasing pixel density only in this specific area through selective distortion compensation. This ensures high detection reliability within the region of interest while maintaining a balance with information loss by preserving the broader field of view context, albeit with lower pixel density.

Inventive Principle:
Principle #3Local quality

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

This approach allows for more reliable detection of obstacles and changes in driver parameters, increasing road safety by providing higher information density in critical regions of the image, thus improving the system's ability to alert drivers to potential hazards and monitor attention levels.

Implementation Method 1

the camera includes an optical lens that causes a distortion of the captured images

Methodology Applied
Scientific EffectOptical distortion: Lens

Data Source

PatentEP4303833A1Driver assistance system
Publication Date: 2024.01.10 HARMAN BECKER AUTOMOTIVE SYST GMBH
  • EP4303833A1 patent drawingFigure 1~2C
  • EP4303833A1 patent drawingFigure 3~4
  • EP4303833A1 patent drawingFigure 5~6

AI summary

A driver assistance system (500) for a vehicle (10), the driver assistance system (500) comprising a camera (502) mounted on the vehicle (10) and configured to capture one or more images inside and/or outside of the vehicle (10), and a processing unit (504), wherein the camera (502) has a defined field of view FOV, the camera (502) comprises an optical lens that causes a distortion of the captured images, the processing unit (504) is configured to perform distortion compensation on the images captured by the camera (502), 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 region of interest ROI is smaller than the field of view FOV of the camera (502).