3D Model Reconstruction Using Laser Pose Estimation
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Solution Overview
Problem
Current computer vision methods for 3D model reconstruction in VR/AR systems face challenges in accurately capturing and reconstructing objects in real-world environments, particularly when the device moves around the target object, leading to inaccuracies and inefficiencies in pose estimation and model generation.
Innovation Solution
The method involves using laser emitters to provide laser beams, a depth camera to capture depth data, and light sensors to detect these beams for obtaining an initial camera pose, which is then used by a processing circuit to perform 3D reconstruction of the target object, employing lighthouse tracking and Iterative Closest Point (ICP) algorithms for accurate pose estimation and model building.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If computer vision methods are used for 3D model reconstruction when the device moves around the target object, then the coverage and completeness of the reconstructed model is improved, but the accuracy of pose estimation and reconstruction precision deteriorate
Solution Approach 1:
The patent introduces laser beams as an intermediary reference system between the moving device and the target object. The laser emitters project structured light patterns that serve as a stable reference framework, while light sensors detect these patterns to calculate device pose. This intermediary laser reference system decouples the pose estimation accuracy from the device's movement, allowing comprehensive coverage while maintaining precision.
Solution Approach 2:
The system performs preliminary pose estimation using laser beam detection before conducting the full 3D reconstruction process. By pre-establishing the device's position and orientation through laser pattern recognition, the system creates an accurate initial pose estimate that guides subsequent depth data capture, ensuring both comprehensive coverage and high reconstruction precision.
2Device complexity
If traditional computer vision methods are used for pose estimation during device movement, then the system complexity is reduced, but the reconstruction accuracy and reliability deteriorate
Solution Approach 1:
The patent introduces laser beams as an intermediary reference system between the moving device and the target object. The laser emitters project structured light patterns that serve as a stable reference framework, while light sensors detect these patterns to calculate device pose. This intermediary laser reference system decouples the pose estimation accuracy from the device's movement, allowing comprehensive coverage while maintaining precision.
Solution Approach 2:
The system changes the reference parameter from visual features in the scene to the controlled laser beam pattern. By using the known, stable geometry of projected laser lines as the reference instead of relying on natural image features, the system achieves higher reliability in pose estimation while adding only moderate complexity through the laser projection and detection components.
3Area of stationary object
If the device moves around the target object to capture comprehensive depth data, then the completeness of the 3D model is improved, but the time consumption increases
Solution Approach 1:
The system performs preliminary pose estimation using laser beam detection before conducting the full 3D reconstruction process. By pre-establishing the device's position and orientation through laser pattern recognition, the system creates an accurate initial pose estimate that guides subsequent depth data capture, ensuring both comprehensive coverage and high reconstruction precision.
Solution Approach 2:
The system uses feedback from light sensor detection of laser patterns to continuously update and refine pose estimation during device movement. This real-time feedback mechanism allows the system to adapt to movement and maintain accurate reconstruction, reducing the need for multiple passes and minimizing total time consumption while ensuring model completeness.
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
This approach enhances the accuracy and speed of 3D model reconstruction, reducing time consumption and improving user experience in VR/AR environments by providing a precise and efficient method for object recognition and integration in mixed reality systems.
Implementation Method 1
capturing, by a depth camera on an electronic device, a depth data of a target object
Implementation Method 2
detecting, by one or more light sensors on the electronic device, the laser beams emitted by the one or more laser emitters
Data Source
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Figure 3A
AI summary
A 3D model reconstruction method includes: providing, by one or more laser emitters, laser beams; capturing, by a depth camera on an electronic device, a depth data of a target object when that the electronic device moves around the target object; detecting, by one or more light sensors on the electronic device, the laser beams emitted by the one or more laser emitters to obtain a camera pose initial value of the depth camera accordingly; and performing, by a processing circuit, a 3D reconstruction of the target object using the depth data based on the camera pose initial value to output a 3D model of the target object.