Camera Orientation Alignment Using Pixel Object Edge Angles
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Solution Overview
Problem
Existing methods for determining the orientation of a camera's extrinsic parameters, particularly in autonomous driving, rely on known object dimensions, which are impractical under real conditions, and lack precision independent of image quality or sharpness.
Innovation Solution
A method that classifies pixel object edges based on real object properties, determining angles between pixel object edges and image axes without assuming object sizes, allowing for precise camera alignment and distortion correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If known object dimensions are used for camera alignment, then camera orientation can be determined, but the method becomes impractical under real conditions where object sizes are unknown
Solution Approach 1:
The invention changes the parameters used for camera alignment from object size-dependent measurements to angle-based measurements. By determining angles between pixel object edges and image axes, and comparing these with angles derived from real object geometry, the method achieves camera orientation determination without requiring knowledge of object dimensions, thus making it adaptable to real-world conditions where object sizes are unknown.
2Measurement precision
If image quality factors such as resolution or sharpness are used for alignment, then alignment accuracy may improve, but the method becomes dependent on image quality rather than geometric properties
Solution Approach 1:
The invention replaces image quality-based alignment methods with a geometric approach. Instead of relying on image resolution or sharpness, the method uses angle measurements between pixel object edges and image axes, comparing these with angles derived from real object geometry. This substitution makes the alignment method reliable and independent of image quality factors.
3Ease of manufacture
If assumptions are made about recorded objects to simplify alignment, then the method becomes easier to implement, but accuracy decreases due to incorrect assumptions
Solution Approach 1:
The invention extracts only the essential geometric properties needed for alignment - specifically angles between object edges and reference planes - while eliminating the need for assumptions about object sizes or types. By classifying pixel objects based on their edge geometry and comparing with real object angle properties, the method achieves both implementation simplicity and high accuracy without requiring incorrect assumptions.
Data Source
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AI summary
Method for determining the orientation of a camera, wherein a pixel-object edge of a recorded pixel-object can be extracted from the image taken by the camera, wherein a pixel-object is classified according to pixel-object properties and according to real object properties, and a pixel-object edge of a pixel-object is selected which pixel-object edge exhibits the real object property of an object that is oriented at a defined real angle to a real horizontal reference plane and/or to a real vertical reference plane.wherein a real camera tilt angle can be determined by determining a first angle between the pixel object edge and the horizontal image axis and/or by determining a second angle between the pixel object edge and the vertical image axis and/or a pixel object is classified according to real object properties and the motion plane is selected from the multitude of pixel objects and a pixel motion plane edge of the motion plane is detected, wherein the pixel position of the pixel motion plane edge is compared with a target pixel position and an offset measure is determined.