Camera Position Analysis with ML Correction Model
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Solution Overview
Problem
Existing position analysis devices and camera systems struggle to accurately measure target positions in subjects from captured images, particularly due to errors in coordinate transformation and lens distortion.
Innovation Solution
A position analysis device and method that includes a processor for calculating coordinate transformation from a camera coordinate system to a subject coordinate system, and a memory for storing a correction model to adjust the transformed position based on reference positions, with weight functions that increase weighting as the transformed position approaches corresponding reference positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If coordinate transformation is performed from camera coordinate system to subject coordinate system, then position measurement is enabled, but measurement precision deteriorates due to transformation errors and lens distortion
Solution Approach 1:
The patent applies preliminary action by pre-calculating correction amounts for coordinate transformation errors and lens distortion before actual position measurement. The system performs calibration to determine correction models in advance, storing correction data that compensates for systematic errors. This allows the measurement system to automatically apply corrections without real-time intervention, improving both precision and reliability.
Solution Approach 2:
The patent utilizes parameter changes by adjusting correction amounts based on distance from reference positions. The correction model dynamically modifies coordinate transformation parameters according to the measured distance, applying larger corrections when distortion is expected to be greater (e.g., at larger distances or angles from the optical axis). This adaptive parameter adjustment optimizes measurement accuracy across different spatial regions.
2Measurement precision
If correction model with multiple reference positions is used, then position accuracy is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the measurement space into multiple regions, each associated with a reference position. Instead of using a single complex correction model for the entire field of view, the system creates multiple simpler correction models, each valid for a specific region. This segmented approach reduces the complexity of individual models while collectively covering the entire measurement area with high accuracy.
Solution Approach 2:
The patent implements partial action by applying correction only in necessary regions and to the extent required. The system determines correction amounts based on distance from reference positions, applying full correction only where needed rather than uniformly across all measurements. This selective correction approach reduces computational complexity while maintaining accuracy where it matters most.
Data Source
AI summary
A position analysis device includes: an input interface that acquires the captured image obtained by the camera; a processor that calculates coordinate transformation from a first coordinate system to a second coordinate system with respect to the target position in the acquired captured image; and a memory that stores a correction model to generate a correction amount of a position in the second system, wherein the processor corrects a transformed position from the target position, based on the correction model wherein the correction model is constructed by machine learning to minimize an error at each reference position.