Heterogeneous Camera Calibration via Dynamic View Transform Vectors
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Solution Overview
Problem
Conventional calibration methods for heterogeneous cameras, such as color and depth cameras, struggle with achieving accurate real-time calibration and handling camera drift, especially when cameras are positioned at different spatial locations, leading to inaccuracies in 3D information extraction.
Innovation Solution
An image processing apparatus and method that calculates view transform vectors for both color and depth cameras by comparing corresponding points between frames using structure form motion and depth point cloud matching processes, and combines these to determine the calibration between the cameras, while utilizing statistical methods to address camera drift and resolution differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional calibration methods using known patterns and extracted corresponding points are used between heterogeneous cameras, then calibration can be performed, but measurement precision and reliability deteriorate due to camera drift and spatial position differences
Solution Approach 1:
The patent implements dynamic calibration by continuously calculating view transform vectors between frames rather than performing static calibration once. The system updates calibration parameters in real-time as cameras move, allowing the calibration to adapt to changing spatial relationships and eliminate drift accumulation.
Solution Approach 2:
The system uses feedback by comparing corresponding points between color and depth images across multiple frames to continuously refine the view transform vector. This closed-loop approach detects deviations caused by camera drift and corrects them through iterative optimization of calibration parameters.
2Loss of information
If heterogeneous cameras (color and depth) are used to obtain accurate 3D information, then information completeness improves, but device complexity increases due to the need for multi-camera calibration
Solution Approach 1:
The patent merges the calibration processes of color and depth cameras by calculating a single view transform vector that transforms points from one camera's coordinate system to the other's. This unified approach reduces complexity compared to calibrating each camera separately while maintaining complete 3D information from both sensor types.
3Productivity
If real-time calibration is implemented between heterogeneous cameras, then productivity improves through continuous operation, but measurement precision may deteriorate due to motion and drift during calibration
Solution Approach 1:
The system performs preliminary feature point extraction and matching within each frame before calculating the view transform vector. By preparing correspondence data in advance and using robust matching algorithms, the system maintains precision even during real-time operation and camera motion.
Solution Approach 2:
The patent maintains continuous calibration by processing each new frame as it arrives, continuously updating the view transform vector without interruption. This continuous action ensures that calibration remains current and accurate throughout operation, preventing drift accumulation while maintaining productivity.
Data Source
AI summary
A first calculator of an image processing apparatus may trace a view transform vector between color images of different frames. A second calculator may trace a view transform vector between depth images of different frames. In this example, a third calculator may calculate a view transform vector between the color camera and the depth camera using the view transform vector between the color images and the view transform vector between the depth images.