Real-time Vehicle Camera Calibration via Vanishing Point Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing Advanced Driver Assistance Systems (ADAS) face challenges in real-time camera calibration, particularly for extrinsic parameters, as most calibration algorithms are not real-time and require complex user actions or special patterns, making them impractical for moving vehicles.
Innovation Solution
A real-time camera calibration system estimates pitch and yaw angles using optical flow and key point tracking on embedded platforms, allowing for automatic calibration by identifying vanishing points from road markings and filtering out irrelevant points to ensure accurate and efficient extrinsic parameter estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional calibration algorithms are used, then calibration accuracy is improved, but real-time performance deteriorates and device complexity increases
Solution Approach 1:
The patent extracts only the essential calibration information (vanishing point coordinates) from the image data, rather than processing complete calibration patterns. By focusing solely on detecting straight lines and their intersections in the image plane, the system obtains sufficient calibration data with minimal processing, achieving both accuracy and real-time performance
Solution Approach 2:
Instead of using complex calibration patterns and algorithms to derive camera parameters, the patent inverts the approach by directly observing natural straight lines in the scene (road markings, building edges) and using their vanishing points to determine calibration. This simplifies the calibration process while maintaining accuracy
2Measurement precision
If traditional calibration algorithms are used, then calibration accuracy is improved, but automation level deteriorates due to complex user actions required
Solution Approach 1:
The calibration system performs self-calibration by automatically detecting straight lines in the captured image and computing vanishing points without human intervention. The algorithm autonomously identifies calibration-relevant features, processes the data, and updates camera parameters, making the entire calibration process fully automated and eliminating the need for user actions with calibration patterns
Solution Approach 2:
The patent makes the calibration system universal by enabling it to use any straight lines visible in the scene for calibration, rather than requiring specific calibration patterns. This allows the system to perform calibration in diverse real-world environments using natural geometric features, greatly enhancing automation and ease of use
3Measurement precision
If comprehensive key point tracking is performed, then calibration quality is improved, but calculation time increases
Solution Approach 1:
The patent applies local quality by focusing computational resources only on regions of the image containing straight lines relevant to calibration (such as road markings or building edges). Rather than processing the entire image uniformly, the system identifies and processes only the local areas containing calibration information, reducing overall calculation time while maintaining calibration quality
Solution Approach 2:
The system performs partial action by tracking only the minimal set of key points necessary to determine vanishing points accurately. Instead of comprehensive tracking of all image features, the algorithm identifies and processes only those straight lines and their intersections that are sufficient for calibration, achieving the necessary calibration quality with reduced computational effort
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
Enables fully automatic, real-time calibration of vehicle cameras while moving, reducing calculation time and increasing calibration quality, ensuring the accuracy of safety features like forward collision warning and lane departure warning systems.
Implementation Method 1
A tracking algorithm tracks key points on the road and obtains trajectories of key points for vanishing point estimation. The tracking algorithm may be based on optical flow calculation of a small subset of relevant points
Data Source
AI summary
A camera facing the front of a vehicle while the vehicle is moving on the road may be calibrated by receiving sequential images from the camera. Image key points in the area limited by the road location are selected. The key points are tracked using an optical flow method. A filtering procedure is applied to the key points to identify the straight-line motion of the vehicle. At least two straight lines corresponding to opposite sides of the road. A calibration algorithm is applied to the at least two lines to determine a vanishing point. The pitch and/or yaw angles of the camera are then calculated.