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  1. Home
  3. Multi-frame Temporal Integration For 3-d Shape Measurement Of Freely Falling Small Objects Using A High-speed Camera Array.
  1. Home
  3. Multi-frame Temporal Integration For 3-d Shape Measurement Of Freely Falling Small Objects Using A High-speed Camera Array.

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

Published on: December 3, 2013

Multi-Frame Temporal Integration for 3-D Shape Measurement of Freely Falling Small Objects Using a High-Speed Camera

Hao Duan1, Shaopeng Hu2, Feiyue Wang3

  • 1Graduate School of Innovation and Practice for Smart Society, Hiroshima University, Higashi-Hiroshima Campus, Higashihiroshima 739-0046, Japan.

Sensors (Basel, Switzerland)
|June 12, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces a multi-frame temporal integration method for 3-D reconstruction of fast-moving objects. By combining images over time, it enhances geometric accuracy without needing more cameras, achieving sub-millimeter precision.

Keywords:
high-speed imagingmillimeter-scale 3-D shape measurementmulti-frame reconstructionvolumetric sensing

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A Protocol for Real-time 3D Single Particle Tracking
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A Protocol for Real-time 3D Single Particle Tracking

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Related Experiment Videos

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

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

Published on: December 3, 2013

A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

Area of Science:

  • Computer Vision
  • 3-D Reconstruction
  • Metrology

Background:

  • High-speed 3-D reconstruction is limited by viewpoint availability in fixed camera arrays.
  • Insufficient viewpoints lead to incomplete or inaccurate geometry in single-frame multi-view stereo.

Purpose of the Study:

  • To develop a multi-frame temporal integration approach for enhanced 3-D reconstruction of moving objects.
  • To overcome the limitations of single-frame reconstruction by leveraging the rigid-body assumption.

Main Methods:

  • Utilized a three-layer circular array of 32 synchronized RGB cameras (1440x1080, 160 fps).
  • Developed a free-fall-oriented algorithm for active frame detection and temporal window selection.
  • Integrated accumulated multi-frame images into a structure-from-motion and multi-view stereo (SfM-MVS) pipeline.
  • Simultaneously recovered object 6-DOF pose trajectory using SfM-estimated camera parameters.

Main Results:

  • Single 32-camera frame achieved an F-score > 0.97 at a 0.5 mm threshold against a structured-light scanner.
  • Temporal frame accumulation reached a plateau F-score of 0.984, with diminishing returns beyond 1-2 frames.
  • Achieved sub-millimeter accuracy (mean error 0.146±0.033 mm, mean relative error ~1.6%) for 8-10 mm objects.
  • Resolved fine surface features like cracks, enabling visual defect identification.

Conclusions:

  • Rigid-body multi-frame temporal integration is effective for high-throughput, non-contact 3-D inspection of small, moving objects.
  • A small number of temporal frames is sufficient for convergent sub-millimeter accuracy.
  • The method enhances viewpoint density without additional hardware, improving reconstruction quality.