Handheld RGB-D Scanner Real-Time 3D Modeling
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Solution Overview
Problem
Conventional image capture systems lack real-time capabilities and intensive image manipulation functionality, particularly in field applications, and fail to provide high-resolution, high-frame-rate 3D imaging with precise object location.
Innovation Solution
A handheld 3D imaging system that combines an RGB-D camera with a portable computer system, enabling real-time capture and processing of images to create precise 3D models, using structured light or Time-of-Flight depth map determination, and software for image manipulation and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional image capture systems are used, then device complexity is reduced, but real-time capability and image manipulation functionality are lost
Solution Approach 1:
The system divides functionality into separate modules: image capture device, depth computation system, spot location system, and handheld computer system. Each module performs a specific function independently, allowing real-time processing while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The handheld imaging system integrates multiple functions into a single portable device: image capture, depth map generation, spot location, 3D model creation, and real-time manipulation. This multi-functionality enables real-time capabilities that conventional single-function devices cannot achieve.
2Measurement precision
If high-resolution 3D imaging is achieved, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines RGB imaging and depth map generation into a single integrated system. The image capture device and depth computation system work together to simultaneously acquire color and depth information, enabling high-precision 3D imaging without requiring separate complex systems for each function.
Solution Approach 2:
The handheld computer system acts as an intermediary that processes data from the image capture device and depth computation system. It coordinates the complex operations of 3D model creation and real-time manipulation, managing system complexity through centralized processing and control.
3Productivity
If real-time 3D model creation is implemented, then productivity is improved, but loss of time in data processing occurs
Solution Approach 1:
The system performs preliminary processing operations continuously during image capture, including depth map generation and initial 3D model construction. By preparing data in advance and updating models incrementally as images are captured, the system eliminates post-processing delays and achieves real-time workflow efficiency.
Solution Approach 2:
The imaging system maintains continuous processing operations throughout the capture sequence. The depth computation system and spot location system operate continuously alongside image capture, ensuring that data processing never pauses or creates delays. This continuous action enables real-time 3D model creation without time loss.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables the creation of high-resolution, real-time 3D models with millimeter accuracy, improving user productivity by streamlining workflows and allowing for immediate data manipulation and visualization.
Implementation Method 1
using structured light or Time-of-Flight depth map determination
Data Source
AI summary
A system and method for real-time or near-real time processing and post-processing of RGB-D image data using a handheld portable device including extracting gray values from the RGB-D image data, creating image pyramids from the grey values and the depth data, computing a scene fitness value using the image pyramids, predicting a camera pose and aligning the image with a first subset of selected key frames, computing a new camera pose estimate and creating a keyframe using the new camera pose estimate, after the keyframe is created, selecting a second subset of keyframes different from the first subset of keyframes and repeating the step of aligning with each keyframe of the second subset of keyframes, deciding whether new links are required to the keyframe in a keyframe pose graph and linking the keyframes.