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Flexible Three-Dimensional Reconstruction via Structured-Light-based Visual Positioning and Global Optimization.

Lei Yin1,2,3, Xiangjun Wang4,5, Yubo Ni6

  • 1State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin 300072, China. zgkdxzylei@163.com.

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Summary
This summary is machine-generated.

This study introduces a novel visual positioning method for line structured light vision systems, eliminating the need for motion constraints. The developed algorithm achieves high 3D reconstruction accuracy, with a point cloud root mean square error within 0.5 mm at 1.5 m.

Keywords:
3D reconstructionglobal optimizationpose estimationstereo visionstructured light

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Area of Science:

  • Computer Vision
  • Robotics
  • Metrology

Background:

  • Traditional 3D reconstruction with line structured light systems relies on motion restraint devices, limiting flexibility.
  • Existing visual localization algorithms often suffer from error accumulation and pose drift.

Purpose of the Study:

  • To propose a motion-constraint-free visual positioning method for line structured light binocular camera systems.
  • To enhance the accuracy and reduce error accumulation in 3D surface reconstruction.

Main Methods:

  • An extended orthogonal iteration algorithm for precise visual positioning of a moving binocular camera system.
  • A global optimization method to calculate camera poses relative to the world coordinate system.
  • Utilizing binocular camera information for improved localization accuracy.

Main Results:

  • The proposed method significantly improves positioning accuracy compared to traditional algorithms.
  • Effective reduction of error accumulation and pose drift during free-moving 3D data acquisition.
  • Experimental validation demonstrating high reconstruction accuracy, with a root mean square error of 0.5 mm at 1.5 m.

Conclusions:

  • The developed free-moving line structured light vision system enables accurate 3D surface measurement without motion constraints.
  • The proposed visual positioning and global optimization methods offer a significant advancement in 3D reconstruction accuracy and system flexibility.