Out-of-Domain Image Screening for 2D-to-3D Pose Estimation
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Solution Overview
Problem
Conventional aerial refueling systems face challenges in accurately estimating the three-dimensional position of objects using two-dimensional input due to deployment conditions that differ from the data used for validation, leading to potential errors.
Innovation Solution
A system that includes a camera, processor, and neural networks to determine a domain score for incoming 2D images, filtering out-of-domain data, and using masked autoencoders and adversarial discriminators to enhance 2D-to-3D pose estimation by predicting semantic keypoints and optimizing 6DOF pose estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single camera is used for 2D input to estimate 3D position, then the system complexity is reduced, but the measurement precision and reliability of the pose estimate deteriorate
Solution Approach 1:
The patent introduces an intermediary domain score verification step between image acquisition and pose estimation. This intermediary mechanism evaluates whether the input image belongs to the training domain before processing, acting as a gatekeeper that prevents out-of-domain images from degrading estimation accuracy while maintaining system simplicity.
Solution Approach 2:
The patent performs preliminary domain score calculation on incoming images before they are processed by the pose estimation system. This preliminary action filters out unsuitable images in advance, ensuring that only in-domain images with reliable characteristics are passed to the estimation algorithm, thereby maintaining high accuracy without requiring complex hardware.
2Productivity
If the system processes all incoming images without domain verification, then the processing speed is maintained, but the reliability of the estimation system deteriorates due to out-of-domain data
Solution Approach 1:
The domain score acts as an intermediary verification layer that quickly assesses image suitability. This lightweight intermediary check adds minimal processing overhead while significantly improving reliability by preventing out-of-domain images from producing erroneous estimates.
Solution Approach 2:
The patent replaces complex mechanical or hardware-based validation mechanisms with a computational domain score assessment. This substitution maintains processing speed by using efficient neural network-based domain classification rather than elaborate physical verification systems.
3Reliability
If domain score verification is added to filter out-of-domain data, then the reliability of pose estimation is improved, but the device complexity increases
Solution Approach 1:
The patent replaces potential complex hardware-based validation systems with a software-based domain score verification mechanism using neural networks. This substitution achieves high reliability through intelligent data assessment rather than elaborate physical or mechanical systems.
Solution Approach 2:
The domain score serves as a simple intermediary that bridges image input and pose estimation without requiring complex system architecture. This intermediary layer adds minimal complexity while providing robust reliability improvement through intelligent filtering.
4Loss of information
If out-of-domain images are processed without filtering, then no data is lost, but the accuracy of the vision position estimation system deteriorates
Solution Approach 1:
The domain score verification acts as an intermediary filter that identifies and separates out-of-domain images from in-domain images. This intermediary mechanism prevents accuracy degradation by excluding unsuitable data while maintaining a clean training and operation dataset.
Solution Approach 2:
The patent extracts and removes out-of-domain images from the processing pipeline using domain score assessment. This extraction of problematic data prevents it from contaminating the estimation results, thereby maintaining high measurement precision without losing valuable in-domain data.
Data Source
AI summary
Disclosed herein are methods, systems, and aircraft for performing image analysis for aiding refueling operations. A method includes receiving a 2D image from a camera, determining a domain score for the 2D image based on previously defined training data, and sending the 2D image to the vision position estimation system in response to the domain score being greater than a predefined threshold, thus creating a sent 2D image.