Research on surface measurement method based on multi-view stereo vision and neutral network calibration

HAN Yukun; PAN Chong; WANG Wentao; LIU Wei

doi:10.11729/syltlx20210048

Volume 35 Issue 6

Dec. 2021

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Article Navigation > Journal of Experiments in Fluid Mechanics > 2021 > 35(6): 44-51

HAN Y K，PAN C，WANG W T，et al. Research on surface measurement method based on multi-view stereo vision and neutral network calibration[J]. Journal of Experiments in Fluid Mechanics, 2021，35（6）：44-51. doi: 10.11729/syltlx20210048

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Research on surface measurement method based on multi-view stereo vision and neutral network calibration

doi: 10.11729/syltlx20210048

HAN Yukun^1
,,
PAN Chong^{1, 2
,
,},
WANG Wentao³,
LIU Wei³

1.
Key Laboratory of Fluid Mechanics of Ministry of Education, Beihang University, Beijing　100191, China
2.
Aircraft and Propulsion Laboratory, Ningbo Institute of Technology, Beihang University, Ningbo Zhejiang　315800, China
3.
The 702nd Research Institute of China Ship Scientific Research Center, Wuxi Jiangsu　214000, China

Received Date: 2021-05-19
Rev Recd Date: 2021-06-17

Available Online: 2021-12-10

Publish Date: 2021-12-30

Abstract

Abstract

Non-contact optical measurement of three-dimensional surface topography is an important application of the computer multi-view stereo vision technology. However, there are still some technical problems needed to be solved such as limited number of cameras, complex image matching algorithms and insufficient longitudinal measurement accuracy. The article develops an optical method for surface topography measurement based on multi-view stereo vision and neural network calibration. This algorithm includes: applying neural networks for the calibration of the multi-view cameras and the three-dimensional reconstruction of feature points, projecting a laser speckle pattern on the surface as the feature points for image recognition and matching, using the particle tracking velocity technology to match the same single feature point in the multi-view images. As proved by experiments, compared with the traditional stereo vision measurement system, which is calibrated based on the pinhole camera model and matched by the epipolar constraint or cross-correlation algorithm, the method proposed in this paper can be adapted to scenes with large optical distortion, besides, the spatial resolution of the surface topography measurement is effectively improved and the measurement error in the depth direction is at the level of 1.0% – 2.0%.
- multi-view stereo vision,
- surfaces topography measurement,
- feature points matching,
- neural networks,
- particle tracking velocity

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References(16)

References

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