Multi-Camera Calibration Using Search-Window Feature Matching
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Solution Overview
Problem
Existing calibration techniques for multiple imaging apparatuses capturing a common three-dimensional space face challenges in accurately calibrating parameters due to significant differences in camera positions and orientations, leading to difficulties in extracting unique feature points and high processing loads.
Innovation Solution
A calibration method that generates search windows using obtained parameters to extract feature points, narrows down candidate feature points based on three-dimensional information, and performs feature point matching to efficiently calibrate imaging apparatus parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If feature point extraction is performed on images captured by multiple imaging apparatuses with different positions and orientations, then calibration accuracy can be improved, but processing load increases significantly
Solution Approach 1:
The patent divides the image into multiple search windows, where each search window is a smaller region containing potential feature points. By segmenting the image this way, the system can process only relevant portions rather than the entire image, reducing processing load while maintaining calibration accuracy through comprehensive feature point extraction across all search windows.
Solution Approach 2:
The patent applies different processing strategies to different regions of the image by creating search windows with specific characteristics tailored to local content. Each search window is designed to capture local feature points with appropriate size and position, allowing optimized processing for each region's specific content while contributing to overall calibration accuracy.
2Measurement precision
If feature point matching is performed between images with significant differences in camera position and orientation, then calibration can be achieved, but matching accuracy decreases due to difficulty in extracting unique feature points
Solution Approach 1:
By segmenting each image into multiple search windows, the system can extract feature points from specific regions that are more likely to contain unique and distinguishable features. This segmentation approach helps overcome the difficulty of extracting unique feature points from images with significant camera position and orientation differences, thereby improving matching accuracy.
Solution Approach 2:
The patent performs preliminary processing by creating search windows before feature point extraction. This preliminary action organizes the image data in advance, guiding the subsequent feature point extraction process to focus on relevant regions. This preliminary organization makes feature point extraction more effective and improves matching accuracy by ensuring that only appropriate feature points are extracted and matched.
Data Source
AI summary
A calibration method of calibrating, using a processor, parameters of a plurality of imaging apparatuses that capture a common three-dimensional space, includes: obtaining images captured by the plurality of imaging apparatuses; obtaining the parameters of the plurality of imaging apparatuses; for each of the images, generating at least one search window to extract a plurality of feature points of the image using the parameters; for each of the images, extracting the plurality of feature points from an inside of the at least one search window; performing feature point matching between the images using the plurality of feature points; and calibrating the parameters based on a plurality of matching results obtained.