3D Position Estimation Using Triangular Camera Epipolar Matching
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Solution Overview
Problem
Conventional systems face challenges in accurately determining the position of an object in a three-dimensional space using multiple cameras due to shifts in camera positions, leading to increased processing time and uncertainty in identifying corresponding positions.
Innovation Solution
A system utilizing three imaging devices arranged in a triangular formation, transforming image data to stereo spherical coordinates, and applying the epipolar constraint to determine if coordinate points correspond to the same object in three-dimensional space, without requiring a fundamental matrix calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple cameras (range sensors) are used to track a customer, then the ability to identify customer position is improved, but the processing time to determine whether position shifts correspond to the same object increases
Solution Approach 1:
The patent introduces spherical image coordinates as an intermediary representation to bridge the gap between multiple camera views. By transforming image coordinates from each camera into a unified spherical coordinate system, the system creates a common reference framework that enables direct comparison and identification of objects across different camera perspectives without time-consuming processing
Solution Approach 2:
The patent changes the parameter space from traditional camera coordinate systems to spherical image coordinates. This parameter transformation allows for efficient comparison of object positions across multiple cameras by converting them into a unified coordinate representation, thereby reducing processing time while maintaining measurement precision
2Area of stationary object
If the positions of objects captured by multiple cameras are shifted, then the coverage area is improved, but the processing time to determine object identity increases
Solution Approach 1:
The patent transitions from two-dimensional image coordinates to three-dimensional spherical image coordinates. This dimensional transformation provides an additional degree of freedom that enables the system to handle position shifts across different camera views while maintaining efficient object identification through the epipolar constraint verification in the unified spherical coordinate space
Data Source
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AI summary
In order to efficiently estimate the position of an object in a three-dimensional space, a position estimation system 10 includes a position estimation device 20 and three imaging devices 30. The three imaging devices 30 are arranged such that imaging positions of the imaging devices 30 form a triangle. The position estimation device 20 acquires images from the three imaging devices 30, performs transformation from image coordinates to stereo spherical image coordinates, then determines whether or not the epipolar constraint is satisfied in each pair of the stereo spherical image coordinates, and, if the epipolar constraint is satisfied, estimates that such coordinate points correspond to the coordinate position of an object P.