Design of binocular vision 3D reconstruction system based on motion recovery

Xin, 王欣 Wang; Kun, 袁坤 Yuan; Xiao, 于晓 Yu; Ming-chao, 章明朝 Zhang

doi:10.3788/ope.20142205.1379

Cited by 2 publications

(1 citation statement)

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“…First of all, divide the speckle area into grids, and select the grid in the middle as the seed point. Then, calculate the correlation minimum of the grid to be matched according to the correlation function to obtain the whole pixel displacement, and then use the quadratic surface fitting algorithm to perform sub-pixel interpolation [14][15] . For the grid with the pixel size (3, 4 or 5), an equation n n × can be listed, and the coefficient of the surface can be solved based on the minimum quadratic multiplication method.…”

Section: Image Sub-region Correlation Matchingmentioning

confidence: 99%

Vibration Detection for Mobile Phone Based on Digital Image Correlation Method

2023

FSST

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To solve the problem of vibration test of mobile phone, a non-contact testing method is proposed based on binocular stereo vision. The method determines the internal parameters of the lens and the external parameters of two industrial cameras by camera calibration. After obtaining the corresponding region between the two cameras by digital image correlation matching, the point coordinates of three-dimensional space are reconstructed based on laser triangulation method, and the vibration of a point with the same name is calculated by tracking its three-dimensional position in adjacent frames. The method has the advantages of non-contact and full-field measurement. The experimental results show that the proposed method has high accuracy. Compared with the measurement results of the vibrometer, the maximum deviation of the proposed method is 0.04 mm and the average deviation is 0.021mm. The proposed method can measure the vibration direction and amplitude of the designated area on the mobile phone, which provides a test method for the verification and optimization of mobile phone vibration technology.

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Section: Image Sub-region Correlation Matchingmentioning

confidence: 99%