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A High Spatial Resolution Depth Sensing Method Based on Binocular Structured Light.

Huimin Yao1, Chenyang Ge2,3, Jianru Xue4,5

  • 1The Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an 710049, China. huimin.yao@stu.xjtu.edu.cn.

Sensors (Basel, Switzerland)
|April 12, 2017
PubMed
Summary

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This summary is machine-generated.

This study introduces a novel depth sensing system using a laser projector and two infrared cameras. The system achieves higher spatial resolution depth information compared to existing technologies like the Kinect.

Area of Science:

  • Computer Vision
  • Robotics
  • 3D Sensing

Background:

  • Depth information is crucial for various applications, but current RGB-D sensors like Kinect have limitations in accuracy and robustness.
  • Existing depth sensing technologies often struggle with high spatial resolution requirements.

Purpose of the Study:

  • To develop an advanced depth sensing system offering superior spatial resolution and robustness.
  • To overcome the trade-off between spatial resolution and matching precision in depth estimation.

Main Methods:

  • A depth sensing system employing a laser projector and two infrared cameras.
  • Utilizing the block-matching algorithm for disparity estimation.
  • Combining binocular and monocular matching modes to enhance spatial resolution without sacrificing precision.
Keywords:
Kinectbinocular structured lightdepth sensingspatial resolutionspeckle pattern

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Main Results:

  • The proposed system achieves higher spatial resolution depth information compared to the Kinect.
  • Depth quality (range image quality) is maintained.
  • The algorithm is implemented on a low-cost platform supporting 1280x960 resolution at 60 fps.

Conclusions:

  • The novel depth sensing system provides a cost-effective solution for high-resolution depth acquisition.
  • This technology offers improved performance for applications demanding accurate and robust depth data.
  • The system's high frame rate and resolution make it suitable for real-time depth image sequences.