Triangular Multi-Camera Disparity Fusion for Reliable Distance Sensing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for determining distance information from images using stereo systems face challenges in assignment errors and require complex post-processing, especially in safety-critical applications where accurate distance detection is necessary.
Innovation Solution
A method utilizing three imaging units arranged in an isosceles triangle geometry to determine distance information by combining similarity values from the images, simplifying the correspondence analysis and reducing computational complexity through aggregation of similarity values before disparity determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex algorithms for correspondence analysis are used in standard stereo systems, then assignment problems are partially reduced, but assignment errors cannot be completely excluded and reliability remains insufficient for safety-critical applications
Solution Approach 1:
The patent combines multiple stereo pairs formed by three imaging units into a single integrated evaluation process. Instead of separately processing two stereo pairs and then merging results (which requires complex post-processing), the invention integrates the correspondence analysis across all three imaging units simultaneously, combining similarity values from multiple epipolar lines in a unified computation that directly yields the disparity.
Solution Approach 2:
The patent transitions from evaluating correspondences along single epipolar lines in traditional stereo systems to simultaneously evaluating correspondences along multiple epipolar lines (first and second epipolar lines) from different stereo pairs. This multi-dimensional approach aggregates similarity values from different geometric perspectives, providing redundant verification and significantly improving measurement reliability without requiring complex sequential post-processing.
2Reliability
If two stereo pairs are used with complementary distance measurements, then assignment problems are reduced, but post-processing complexity significantly increases
Solution Approach 1:
The patent merges the evaluation of both stereo pairs into a single integrated process. The image processing unit simultaneously determines first similarity values along a first epipolar line from the first stereo pair and second similarity values along a second epipolar line from the second stereo pair, then combines these similarity values in a unified computation to directly determine the common disparity, eliminating the need for separate distance measurements and complex post-processing merging operations.
Solution Approach 2:
The patent performs preliminary aggregation of similarity values from multiple stereo pairs before the actual disparity determination. By pre-combining the similarity values from both epipolar lines during the correspondence analysis phase itself (rather than after separate distance calculations), the system prepares integrated evaluation data that directly leads to the final disparity result, simplifying the overall computational workflow.
3Measurement precision
If complex post-processing is applied to verify distance measurements from multiple stereo pairs, then measurement accuracy is improved, but processing time and computational load increase
Solution Approach 1:
The patent combines the verification function into the primary correspondence analysis process itself. By aggregating similarity values from multiple epipolar lines during the single disparity determination step, the system performs verification and distance calculation simultaneously in one integrated computation, rather than requiring separate verification and post-processing steps that would increase processing time.
Solution Approach 2:
The patent maintains continuous useful action by performing correspondence analysis and disparity determination in a single uninterrupted computational flow. The aggregation of similarity values from multiple stereo pairs occurs continuously during the disparity search process, allowing the system to achieve verified accurate measurements without interrupting the primary measurement workflow for separate verification passes.
Data Source
AI summary
A method includes defining a disparity range having discrete disparities and taking first, second, and third images of a spatial region using first, second, and third imaging units. The imaging units are arranged in an isosceles triangle geometry. The method includes determining first similarity values for a pixel of the first image for all the discrete disparities along a first epipolar line associated with the pixel in the second image. The method includes determining second similarity values for the pixel for all discrete disparities along a second epipolar line associated with the pixel in the third image. The method includes combining the first and second similarity values and determining a common disparity based on the combined similarity values. The method includes determining a distance to a point within the spatial region for the pixel from the common disparity and the isosceles triangle geometry.