Extrinsic Calibration Reference Point Selection Using Epipolar Geometry
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Solution Overview
Problem
The process of extrinsic parameter calibration for vehicle-mounted image sensors is complex and time-consuming due to differences in sensor mounting locations and non-linear distortion in wide-angle lens cameras, making it difficult to locate corresponding 3-space reference points across different perspectives.
Innovation Solution
A method using a processor to select a preliminary reference point at the intersection or vanishing point of straight line feature edges in overlapping image frames, employing epipolar geometry to confirm actual 3-space points for calibration, without the need for dedicated calibration structures, reducing the complexity and time required for reference point selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dedicated calibration structures with known geometry are used, then calibration accuracy is improved, but device complexity and calibration time increase
Solution Approach 1:
The method enables image sensors to perform self-calibration by automatically selecting reference points from natural scene features (straight line intersections and vanishing points) without requiring external calibration structures. The sensors use their own captured images and epipolar geometry relationships to identify valid reference points, making the calibration process self-contained and eliminating the need for complex dedicated calibration equipment.
Solution Approach 2:
The patent replaces expensive, complex dedicated calibration structures with simple, naturally occurring scene features such as straight line intersections and vanishing points in the environment. These natural features serve as temporary calibration references that are easily accessible and require no special equipment, effectively using 'disposable' environmental elements instead of permanent calibration infrastructure.
2Reliability
If traditional reference point selection methods are used, then calibration can be performed, but the process is time-consuming and complex
Solution Approach 1:
The method performs preliminary filtering of potential reference points by automatically identifying straight line feature edges and their intersections in the captured images. By pre-processing the image data to extract geometric features and validate them against epipolar constraints before actual calibration computation, the method reduces the time required during the critical calibration phase while maintaining reliability through systematic validation.
Solution Approach 2:
The patent replaces manual or complex mechanical calibration procedures with automated computational image processing. The system uses algorithms to detect straight lines, find intersections, determine vanishing points, and validate reference points based on epipolar geometry, substituting automated computer vision techniques for traditional manual calibration methods and significantly reducing calibration time.
3Area of stationary object
If wide-angle lens cameras are used to capture broader perspectives, then field of view is improved, but non-linear distortion increases making reference point location more difficult
Solution Approach 1:
The method adapts to the non-linear distortion characteristics of wide-angle lenses by using geometric invariants that remain consistent despite distortion. By focusing on vanishing points and straight line intersections - features that maintain their geometric relationships even under wide-angle projection - the system changes the approach from detecting absolute positions to detecting relative geometric constraints that are invariant to the lens distortion parameters.
Solution Approach 2:
The patent introduces epipolar geometry as an intermediary framework that bridges the gap between distorted wide-angle images and accurate 3D spatial relationships. By using epipolar lines and constraints as a mediator, the system can reliably locate corresponding reference points across differently distorted images from multiple sensors, overcoming the challenges posed by non-linear lens distortion.
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 simplifies the selection of reliable calibration reference points, reducing the overall extrinsic parameter calibration time and improving accuracy by leveraging epipolar geometry to identify actual intersection points and eliminate non-intersection points, thus facilitating more efficient calibration processes.
Implementation Method 1
employing epipolar geometry to confirm actual 3-space points for calibration
Data Source
Figure 1A~1B
Figure 2
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AI summary
A method for selecting a reference point for extrinsic parameter calibration of at least a first or second image sensor is provided. The method comprises selecting by a processor a preliminary reference point which is located at the intersection point or vanishing point of two straight line feature edges appearing in a first and second image frame captured by the first and second image sensor. The processor then determines a first epipolar line corresponding to a first reference image point of the preliminary reference point in the first image, the first epipolar line being located on an image plane of the second image sensor. The processor also determines if the first epipolar line intersects a second reference image point of the preliminary reference point in the second image frame.