Stereo Camera Frontoparallelity Parameter Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing driver assistance systems using stereo camera systems face challenges in accurately determining the distance and orientation of objects, particularly in scenarios where frontoparallelity is violated, such as with roadway markings and guardrails, leading to potential false detections and unsafe driving maneuvers.
Innovation Solution
A method and device that utilize a stereo camera system to form a cost function by comparing images from two cameras, determining a frontoparallelity parameter through a global minimum of the cost function, and using this parameter to control the driver assistance system, allowing for accurate detection of object distances and orientations while being resistant to noise and computational intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional stereo camera systems are used to determine object distance and orientation, then the system can provide basic driver assistance, but the measurement precision deteriorates when frontoparallelity is violated (e.g., with roadway markings and guardrails)
Solution Approach 1:
The patent changes the evaluation parameter from simple disparity matching to a cost function that incorporates frontoparallelity constraints. By modifying the parameters used in cost function evaluation to account for expected frontoparallel orientations, the system achieves reliable detection even when objects violate standard frontoparallel assumptions, directly resolving the measurement precision and reliability contradiction.
2Measurement precision
If complex algorithms are used to improve detection accuracy, then measurement precision improves, but computational intensity increases
Solution Approach 1:
The patent applies preliminary action by pre-defining cost function templates and frontoparallelity constraints based on expected object orientations. These pre-computed parameters are then reused during real-time processing, reducing the computational burden while maintaining high measurement precision. The system prepares evaluation criteria in advance rather than computing them dynamically for each object detection task.
3Reliability
If noise-resistant detection methods are implemented, then detection reliability improves, but device complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where the cost function evaluation provides continuous feedback on detection quality and frontoparallelity compliance. This feedback loop allows the system to adjust detection parameters and filter noisy measurements dynamically, improving reliability without requiring complex additional hardware or system architecture. The feedback-driven approach maintains simplicity while enhancing noise resistance.
Data Source
AI summary
A method for controlling a driver assistance system by using a stereo camera system having a first and a second camera, the method having a step of reading in, a first image being read in from the first camera and a second image being read in from the second camera. The method furthermore comprises a step of forming, a cost function being generated by using the first and the second image. Furthermore, in a further method step of determining, a frontoparallelity parameter representing the frontoparallelity of an object with respect to the stereo camera system is determined by using a global minimum of the cost function. Finally, the method comprises a step of using, the frontoparallelity parameter being used to control the driver assistance system.