Camera Calibration Using Vehicle Body Area Detection
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Solution Overview
Problem
The accuracy of vanishing points is lowered due to image distortion while a vehicle is driving, making it difficult to accurately estimate the vanishing line and subsequently the camera posture.
Innovation Solution
A camera calibration method and apparatus that detect the vehicle body area in an image captured by a vehicle's camera, estimate the camera posture based on the slope of the vehicle body area's edge, and perform image recognition on a calibrated image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If vanishing points and lines are used to estimate camera posture, then the method is simple to implement, but the accuracy deteriorates due to image distortion and vehicle behavior bounding
Solution Approach 1:
The patent changes the reference parameter from vanishing points (which are affected by distortion) to the vehicle body area (which has known geometric properties). By using the vehicle's own structure as a reference frame and detecting its area and edge slopes in the image, the system transforms the problem from one dependent on distant vanishing points to one based on nearby, well-defined vehicle features, thereby improving accuracy while maintaining implementation simplicity
Solution Approach 2:
The vehicle body area serves as an intermediary reference object between the camera and the external scene. Instead of directly using vanishing points from the environment (which are distorted), the system introduces the vehicle's own body area as a mediator with known geometric characteristics, allowing accurate posture estimation through edge slope detection of this intermediate reference
2Ease of operation
If vanishing points are used for calibration, then the process is straightforward, but reliability deteriorates under image distortion conditions
Solution Approach 1:
The patent replaces the vanishing point parameter with vehicle body area parameters (area detection and edge slope). This parameter change makes the calibration more reliable because vehicle edges provide stronger, more distortion-resistant geometric cues compared to vanishing points, while the overall process remains straightforward and easy to operate
Solution Approach 2:
The system performs preliminary detection of the vehicle body area and its edges before proceeding to posture estimation. By pre-identifying the vehicle boundaries and calculating edge slopes in advance, the system prepares a robust reference framework that is less susceptible to distortion effects, thereby improving reliability while keeping the operation simple
Data Source
AI summary
A camera calibration method comprises receiving an image captured by a camera of a vehicle, detecting a vehicle body area of the vehicle from the image, and estimating a posture of the camera based on the vehicle body area.