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Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

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3D Reconstruction Using 3D Registration-Based ToF-Stereo Fusion.

Sukwoo Jung¹, Youn-Sung Lee¹, Yunju Lee¹

¹Contents Convergence Research Center, Korea Electronics Technology Institute, Seoul 03924, Korea.

Sensors (Basel, Switzerland)

|November 11, 2022

Summary

This study enhances 3D reconstruction accuracy by fusing stereo and Time-of-Flight (ToF) sensor data. Complementary sensor fusion improves depth map precision for applications like Augmented Reality (AR) and Extended Reality (XR).

Keywords:

3D reconstruction ToF camera sensor fusion stereo camera

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Area of Science:

Computer Vision
3D Sensing Technologies
Robotics and Perception

Background:

Accurate depth sensing is crucial for immersive technologies like Augmented Reality (AR), Extended Reality (XR), and the Metaverse.
Traditional depth acquisition methods using stereo cameras or Time-of-Flight (ToF) sensors have limitations in accuracy and completeness.
Integrating multiple depth sensing modalities offers a promising approach to overcome individual sensor drawbacks.

Purpose of the Study:

To develop and validate a novel sensor fusion technique for enhanced 3D reconstruction accuracy.
To improve the quality of depth maps by combining stereo vision and ToF sensing.
To generate high-fidelity 3D mesh data from fused sensor inputs.

Main Methods:

A generalized multi-camera calibration method incorporating both color and depth data was employed.
Depth maps from stereo and ToF sensors were fused using 3D registration and reprojection techniques.
Hole-filling algorithms refined the fused depth map, followed by surface reconstruction for mesh generation.

Main Results:

The proposed ToF-stereo fusion method significantly improved depth map accuracy compared to individual sensors.
Hole-filling effectively addressed data gaps in the fused depth map.
The final mesh data demonstrated high fidelity and accuracy in real-world tests.

Conclusions:

Complementary fusion of stereo and ToF depth data provides superior 3D information accuracy.
The developed pipeline offers a robust solution for high-quality 3D reconstruction in AR/XR applications.
The method's efficiency was validated through comparative analysis with existing algorithms.