Camera Parameter Estimation Using Vehicle Motion Vectors
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Solution Overview
Problem
Conventional camera parameter estimation technologies rely on pre-stored data of specific road surface markings, limiting flexibility and accuracy in estimating camera parameters for in-vehicle cameras.
Innovation Solution
A system that calculates vectors corresponding to the traveling direction, normal direction, and orthogonal vectors based on the transition of the camera's position, allowing for flexible estimation of camera parameters without relying on specific road surface markings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pre-stored data of specific road surface markings is used for camera parameter estimation, then the estimation process can be performed, but the flexibility and adaptability to various road conditions deteriorates
Solution Approach 1:
The system uses the vehicle's own motion information (acceleration, steering angle) and captured images to self-calibrate camera parameters without requiring external reference markings or pre-stored data. The camera parameter estimation unit calculates parameters by analyzing the relationship between vehicle motion and image frame transitions, enabling the system to adapt to any road condition automatically.
Solution Approach 2:
The system changes the approach from using fixed pre-stored marking data to dynamically calculating camera parameters based on real-time vehicle motion parameters (acceleration, steering angle) and image data. This parameter change enables adaptation to various road conditions while maintaining estimation accuracy through physics-based calculations.
2Measurement precision
If conventional matching methods with pre-stored regular data are used, then camera parameters can be estimated, but the device complexity and data storage requirements increase
Solution Approach 1:
The invention extracts only the essential information needed for calibration - vehicle motion parameters (acceleration, steering angle) and image frame data - removing the need for complex pre-stored marking databases and matching algorithms. This extraction simplifies the system while maintaining calibration capability.
Solution Approach 2:
The system replaces the mechanical/data-intensive approach of storing and matching marking patterns with a computational approach using vehicle motion sensors and image processing. This substitution eliminates the need for large data storage systems and complex matching algorithms.
3Measurement precision
If specific road surface markings are required for calibration, then camera parameters can be estimated, but the ease of operation and calibration process simplicity deteriorates
Solution Approach 1:
The calibration process becomes self-service by using the vehicle's own motion and captured images to automatically calculate camera parameters. The camera parameter estimation unit performs the calibration without requiring operators to locate or input information about specific road markings, greatly simplifying the operation.
Solution Approach 2:
The system performs preliminary acquisition of vehicle motion parameters (acceleration, steering angle) and image data before the actual parameter estimation. This preliminary action prepares all necessary information in advance, making the final calibration step simple and automatic without requiring manual intervention to find or input marking information.
Data Source
AI summary
A camera parameter estimating device includes: a camera position posture acquisition unit acquiring estimated position and posture of a camera, based on a captured image acquired by the camera; a first vector calculation unit calculating a first vector corresponding to a traveling direction of the vehicle; a second vector calculation unit calculating a second vector corresponding to a normal direction of a plane corresponding to a road surface on which the vehicle travels; a third vector calculation unit calculating a third vector orthogonal to the first and second vectors; and a camera parameter estimation unit estimating an actual installation posture of the camera on the basis of the first, second and third vectors and the estimated posture of the camera when the estimated position moves along a direction indicated by the first vector.