3D Imaging System Automated Feature Registration
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Solution Overview
Problem
Existing 3D modeling systems face challenges in creating accurate and photo-realistic models of environments and objects due to limitations in sensor field of view, resolution, and the need for manual feature selection and registration, which is labor-intensive and less accurate, especially in applications like underground mine mapping where accurate registration with mine maps is difficult.
Innovation Solution
A method and apparatus using a mobile stereo camera system that acquires overlapping successive stereo images, detects features, computes 3D positions, and automatically registers data without external tracking devices, allowing for photo-realistic 3D model creation and integration with additional sensors for enhanced fidelity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual feature selection and registration is used, then accuracy of feature matching is improved, but labor intensity and time consumption increase
Solution Approach 1:
The system automatically detects and matches features across multiple views without human intervention. The computer-implemented algorithm performs feature selection, extraction, and registration autonomously, eliminating the need for manual operation while maintaining high accuracy through sophisticated image processing techniques.
Solution Approach 2:
Manual feature matching operations are replaced by automated computer vision algorithms. The system uses digital image processing, feature detection algorithms, and automatic registration methods to substitute human manual work, achieving both speed and accuracy through computational power rather than human effort.
2Device complexity
If a single sensor is used, then device complexity is reduced, but resolution and depth of field coverage are insufficient
Solution Approach 1:
The system integrates multiple sensor types (stereo cameras, rangefinders, and other sensors) into a single multi-functional platform that can capture both high-resolution imagery and depth information simultaneously. This universal sensor system handles diverse measurement requirements without requiring separate dedicated devices for each function.
Solution Approach 2:
Multiple sensor systems are merged into an integrated multi-sensor platform. The stereo camera system combines two or more cameras with known spatial relationships, and can be further integrated with rangefinders and other sensors to create a unified system that captures comprehensive 3D data with high resolution and extended depth of field.
3Measurement precision
If external tracking devices are used for registration, then registration accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The system performs self-registration by automatically detecting and matching features directly from the captured images without requiring external tracking devices. The computer-implemented algorithm uses natural features in the scene to establish geometric relationships and register multiple views autonomously, eliminating dependence on external positioning systems.
Solution Approach 2:
The system extracts registration information directly from the image data itself rather than relying on separate external tracking systems. Feature points, edges, and other geometric characteristics are extracted from the images to provide the necessary registration data, separating the registration function from external hardware dependencies.
4Productivity
If automatic feature matching algorithms are used, then productivity is improved, but accuracy and reliability decrease
Solution Approach 1:
The system incorporates feedback mechanisms where the automatic feature matching algorithm continuously refines its results by evaluating match quality, adjusting parameters, and iteratively improving registration accuracy. The system uses feedback from multiple views and redundant feature matches to verify and correct automatic matching results, ensuring both speed and reliability.
Solution Approach 2:
The system replaces manual feature matching with sophisticated computer vision algorithms that automatically detect, describe, and match features across images. This substitution maintains high productivity through automation while improving reliability through algorithmic consistency and the ability to process large numbers of features systematically without human error.
Data Source
AI summary
A system for creating photorealistic 3D models of environments and/or objects from a plurality of stereo images obtained from a mobile stereo camera and optional monocular cameras, for enhancing 3D models of environments or objects by registering information from additional sensors to improve model fidelity or to augment it with supplementary information using a light pattern projector, and for generating photo-realistic 3D models of underground environments such as tunnels, mines, voids and caves, including automatic registration of the 3D models with pre-existing underground maps. The cameras may be handheld, mounted on a mobile platform, manipulator or a positioning device. The system automatically detects and tracks features in image sequences and self-references the stereo camera in 6 degrees of freedom by matching the features to a database to track the camera motion, while building the database simultaneously. A motion estimate may be provided from external sensors and fused with the motion computed from the images.