Camera Extrinsic Calibration Using Scene Lines
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Solution Overview
Problem
Existing camera calibration methods require multiple images and are affected by changes in camera position and calibration target positions, making them complex and resource-intensive.
Innovation Solution
A method that determines extrinsic calibration parameters using a single image from each camera, aligning the camera reference frame with the vehicle reference frame by identifying common features and using a Hough accumulator algorithm to determine the ground plane, allowing for real-time operation and correction of camera shifts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are used for camera calibration, then measurement precision may be improved, but device complexity and resource requirements increase
Solution Approach 1:
The patent extracts and utilizes only the essential information needed for calibration from the image data - specifically lines and vanishing points - rather than processing multiple complete images through complex algorithms. This extraction approach maintains calibration accuracy while simplifying the overall process.
Solution Approach 2:
The method performs preliminary detection of lines and vanishing points in the image before proceeding with calibration parameter calculation. By pre-identifying these key geometric features, the calibration process becomes more efficient and less complex while maintaining precision.
2Measurement precision
If multiple images and calibration targets are used, then calibration accuracy may be improved, but loss of time and resource consumption increase
Solution Approach 1:
The patent extracts only the necessary geometric information (lines and vanishing points) from a single image for calibration, eliminating the time-consuming process of capturing and processing multiple images with calibration targets. This extraction methodology achieves accurate extrinsic parameter determination while significantly reducing calibration time.
Solution Approach 2:
The method uses naturally occurring lines in the scene (such as road markings, building edges) as calibration references instead of requiring external calibration targets. The environment itself provides the calibration information, eliminating the need for separate calibration target objects and reducing overall calibration time.
3Measurement precision
If calibration targets and multiple images are used, then measurement precision improves, but ease of operation deteriorates
Solution Approach 1:
The calibration method uses lines that are naturally present in the scene (road markings, architectural features) rather than requiring external calibration targets. This self-service approach allows the calibration to be performed using the environment's own features, greatly simplifying operation while maintaining precision through vanishing point detection.
Solution Approach 2:
The patent extracts calibration information directly from scene lines and geometric features visible in the image, eliminating the need to physically handle, position, or manage calibration targets. This extraction from existing scene elements makes the calibration process much easier to operate while preserving measurement accuracy.
Data Source
AI summary
The application provides a method of calibrating a camera of a vehicle. The vehicle has a reference frame. The method comprises taking an image of a scene by the camera. The ground plane of the vehicle is then determined according to features of the image. An origin point of the vehicle reference frame is later defined as being located on the determined ground plane. A translation of a reference frame of the camera is afterward determined for aligning the camera reference frame with the vehicle reference frame.