Conjugate Point Search Range Optimization via Epipolar Geometry
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Solution Overview
Problem
Current methods for conjugate point matching in photogrammetric analysis, particularly for panoramic images, face challenges in determining an accurate search range due to varying distances of targets from the camera, leading to inefficient computation and incorrect matches.
Innovation Solution
The proposed solution involves defining a search range using an intra-overlap area between images captured by adjacent cameras, which narrows the search range and reduces computation time and incorrect matches by estimating a distance range from the camera position to the conjugate point, allowing for efficient identification of conjugate points in panoramic images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the search range is reduced arbitrarily to decrease computation time, then computation time is reduced, but the accuracy of conjugate point matching deteriorates due to incorrect search range
Solution Approach 1:
The patent performs preliminary actions by calculating the epipolar line and determining the search range before conducting conjugate point matching. This preliminary calculation of the search range based on epipolar geometry ensures that the matching process operates within accurate boundaries, preventing both excessive computation time and incorrect matches.
Solution Approach 2:
The patent changes the parameter of search range from an arbitrary fixed value to a dynamically determined value based on epipolar line calculations. By adjusting the search range parameters according to the specific geometric relationships in each image pair, the system achieves both computational efficiency and matching accuracy.
2Reliability
If the search range is increased to improve the possibility of finding correct conjugate points, then the likelihood of correct match is improved, but computation time increases due to larger number of pixels to compare
Solution Approach 1:
The patent dynamically adjusts the search range parameters based on epipolar line calculations, ensuring the search area is neither too small to miss correct matches nor too large to cause excessive computation. This parameter optimization maintains matching reliability while controlling computation time.
Solution Approach 2:
The patent replaces brute-force comparison across the entire image with a geometrically-constrained search along the epipolar line. This substitution of mechanical pixel-by-pixel comparison with geometric reasoning significantly reduces the search space while maintaining reliability.
3Measurement precision
If area based matching is used to achieve accurate conjugate point identification, then matching accuracy is improved, but the requirement for very accurate initial position of conjugate candidates increases complexity
Solution Approach 1:
The patent replaces complex area-based matching methods with a simpler epipolar line-based approach. By using geometric constraints to define the search range, the system achieves accurate conjugate point identification without requiring very accurate initial positions or complex preprocessing.
Solution Approach 2:
The patent changes the approach from area-based search to line-based search by utilizing epipolar geometry. This parameter change from two-dimensional area search to one-dimensional line search simplifies the method while maintaining accuracy.
4Device complexity
If feature based matching is used to avoid determining search range, then the complexity of search range determination is reduced, but the methods fail when the area of conjugate points cannot be predicted
Solution Approach 1:
The patent replaces feature-based assumption methods with epipolar line-based geometric calculation. This substitution allows the system to determine search ranges reliably without assuming prior knowledge of conjugate point locations, working effectively for both aerial and panoramic images.
Solution Approach 2:
The patent changes from assuming known conjugate point areas to calculating search ranges based on epipolar geometry parameters. This parameter transformation enables reliable search range determination across different image types without requiring predictive information about conjugate point locations.
Data Source
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Figure 3A~3C
AI summary
Tools and techniques for defining a search range for conjugate points in a set of images. In one technique, an intra-overlap area in two images can be used to define a search range in which a conjugate point can be found; in an aspect, this search range might be expressed as a distance range from a station at which one or both of the two images were captured. That distance range can be used to narrow the search range in an image captured from another station, substantially reducing both the computation time to identify a conjugate match and the likelihood of identifying an incorrect match.