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Related Experiment Video

Updated: Aug 25, 2025

Rapid Acquisition of 3D Images Using High-resolution Episcopic Microscopy

Rapid Acquisition of 3D Images Using High-resolution Episcopic Microscopy

Published on: November 21, 2016

Single-shot 3D shape acquisition using a learning-based structured-light technique.

Andrew-Hieu Nguyen, Khanh L Ly, Charlotte Qiong Li

|October 18, 2022

Summary

This summary is machine-generated.

This study introduces an accurate method for 3D shape acquisition from single 2D images by combining structured-light techniques with deep learning. The approach enhances measurement accuracy for 3D shape representation in computer vision applications.

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Last Updated: Aug 25, 2025

Rapid Acquisition of 3D Images Using High-resolution Episcopic Microscopy

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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

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Determining 3D Flow Fields via Multi-camera Light Field Imaging

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Published on: March 6, 2013

Area of Science:

Computer Vision
Deep Learning
3D Shape Acquisition

Background:

Accurate 3D shape acquisition from single images remains challenging.
Existing methods struggle with measurement accuracy in dynamic applications.

Purpose of the Study:

To develop an accurate 3D shape acquisition method from single 2D images.
To integrate structured-light techniques with deep learning for improved 3D reconstruction.

Main Methods:

A pattern-to-pattern deep learning network converts single structured-light images into fringe patterns.
Fringe projection profilometry is used for generating training data and final 3D reconstruction.

Main Results:

The proposed method achieves accurate 3D shape acquisition from single-shot 2D images.
Demonstrated practicality and potential for scientific research and industrial applications.

Conclusions:

The integrated approach overcomes limitations of direct 2D-to-3D transformation.
This technique offers a promising solution for precise 3D shape representation.