Camera Calibration Using Vertical Markers and Bird's Eye View
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Solution Overview
Problem
Existing camera calibration methods for vehicles require extensive space and cumbersome setup, as they necessitate arranging calibration targets on the road surface or precise physical fixation of targets and vehicles, which complicates the measurement process.
Innovation Solution
A calibration method using vertically or horizontally positioned markers above the road surface, where images are captured, converted into bird's eye view, and camera parameters are calculated based on marker positions, eliminating the need for extensive space and precise positional relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If calibration targets are placed on the road surface in a predetermined positional relationship, then measurement accuracy is improved, but the measurement space required becomes several times larger than the vehicle space
Solution Approach 1:
The patent transitions from placing calibration targets on the road surface (2D plane) to suspending them vertically in space (3D space). By utilizing the vertical dimension and positioning targets at different heights above the road surface, the system achieves accurate calibration without requiring extensive horizontal measurement space, thus resolving the contradiction between measurement accuracy and space requirement.
Solution Approach 2:
The patent changes the positional parameters of calibration targets from horizontal arrangement on the road surface to vertical suspension in air. By adjusting the height parameter and spatial configuration of targets, the system maintains measurement accuracy while significantly reducing the required measurement area.
2Area of stationary object
If targets are arranged vertically at a height from the road surface, then the measurement space is saved, but it becomes necessary to physically fix the vehicle and target or adjust target position using scope means
Solution Approach 1:
The patent replaces mechanical fixation systems (joints, physical mounting) and optical adjustment systems (scope means) with a computational approach. By using image processing and coordinate transformation algorithms, the system determines the positional relationship between the camera and calibration targets without requiring physical fixation or manual adjustment, thus simplifying the measurement operation.
Solution Approach 2:
The system performs self-calibration by automatically capturing images of vertically positioned targets and computing the camera's attitude parameters through image processing. The calibration process is autonomous, requiring no manual intervention for physical fixation or position adjustment, making the operation simpler and more efficient.
3Measurement precision
If joints or scope means are used to establish predetermined positional relationship, then measurement accuracy is maintained, but the device complexity and operational complexity increase
Solution Approach 1:
The patent eliminates mechanical joints and optical scope means by using computational methods. The system captures images of calibration targets and uses image processing algorithms to calculate the camera's attitude parameters, replacing complex mechanical and optical systems with a simpler computational approach that maintains measurement accuracy.
Solution Approach 2:
The system creates a digital representation (image) of the calibration targets and uses this copy to compute positional relationships. By working with image data and coordinate transformations rather than physical mechanical systems, the patent simplifies the device complexity while preserving measurement precision.
Data Source
AI summary
A calibration method for calibrating an attitude of a camera mounted on a vehicle using markers each arranged vertically and each positioned at a pre-designated height from a road surface. The method includes: a first process including shooting an image of the markers with the camera, thereby generating a two-dimensional image; a second process including converting the two-dimensional image into a bird's eye view image on a specific plane so that the bird's eye view image reflects the height of each of the markers; and a third process including calculating a parameter of the camera based on a position difference between the markers in the specific plane obtained in the second process.