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3D Transparent Object Detection and Reconstruction Based on Passive Mode Single-Pixel Imaging.

Anumol Mathai1, Ningqun Guo1, Dong Liu2

  • 1School of Engineering, Monash University Malaysia, Jalan Lagoon Selatan, Bandar Sunway, Selangor 47500, Malaysia.

Sensors (Basel, Switzerland)
|August 6, 2020
PubMed
Summary

This study presents a cost-effective method for 3D transparent object reconstruction using a fixed multi-viewpoint approach and single-pixel imaging. The technique accurately determines object shape without needing to know the refractive index, even for complex forms.

Keywords:
compressive sensingdisparity map acquisitionsingle-pixel imagingtransparent object detection

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Area of Science:

  • Computer Vision
  • Optical Metrology
  • 3D Reconstruction

Background:

  • Reconstructing transparent objects is challenging due to light interaction complexities, rendering traditional methods ineffective.
  • Existing techniques often fail with transparent materials, necessitating novel approaches for accurate shape determination.

Purpose of the Study:

  • To develop a cost-effective, fixed multi-viewpoint system for 3D transparent object detection and reconstruction.
  • To overcome limitations of Lambertian surface methods when applied to transparent objects.
  • To enable shape recovery without object movement or knowledge of refractive index.

Main Methods:

  • A fixed multi-viewpoint system utilizing two single-pixel detectors and a digital micromirror device.
  • Projection of binary patterns and implementation of a dark framework to enhance boundary detection.
  • Light path triangulation to recover surface shape, disregarding reflections and refractions.
  • Integration of compressive sensing to reduce data acquisition requirements.

Main Results:

  • Successful 3D reconstruction of transparent objects with complex shapes and unknown refractive indices.
  • High-quality 2D images (32x32 resolution) obtained from single-pixel detectors.
  • Feasibility and accuracy demonstrated through disparity and error maps.

Conclusions:

  • The proposed single-pixel imaging technique offers an affordable and effective solution for 3D transparent object reconstruction.
  • The method's ability to handle complex shapes and unknown refractive indices opens new avenues in optical metrology.
  • This work advances transparent object detection and reconstruction with a simplified, low-cost experimental setup.