DOE-based structured-light method for accurate 3D sensing

2019 ◽  
Vol 120 ◽  
pp. 21-30 ◽  
Author(s):  
Zhan Song ◽  
Suming Tang ◽  
Feifei Gu ◽  
Chu Shi ◽  
Jianyang Feng
Keyword(s):  
2014 ◽  
Vol 55 ◽  
pp. 113-127 ◽  
Author(s):  
Min Young Kim ◽  
Shirazi Muhammad Ayaz ◽  
Jaechan Park ◽  
YoungJun Roh

2020 ◽  
Vol 20 (17) ◽  
pp. 9796-9805
Author(s):  
Yuehua Li ◽  
Jingbo Zhou ◽  
Qingwei Mao ◽  
Jiangyan Jin ◽  
Fengshan Huang

2014 ◽  
pp. 181-213
Author(s):  
Tyler Bell ◽  
Nikolaus Karpinsky ◽  
Song Zhang

AIP Advances ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 105016 ◽  
Author(s):  
J. Cheng ◽  
Xueping Sun ◽  
Shun Zhou ◽  
Xinxin Pu ◽  
Naitao Xu ◽  
...  
Keyword(s):  

Author(s):  
Qingzeng Ma ◽  
Dongbin Zhang ◽  
Shuo Jin ◽  
Yuan Ren ◽  
Wei Cheng ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Jianying Yuan ◽  
Qiong Wang ◽  
Xiaoliang Jiang ◽  
Bailin Li

The multiview 3D data registration precision will decrease with the increasing number of registrations when measuring a large scale object using structured light scanning. In this paper, we propose a high-precision registration method based on multiple view geometry theory in order to solve this problem. First, a multiview network is constructed during the scanning process. The bundle adjustment method from digital close range photogrammetry is used to optimize the multiview network to obtain high-precision global control points. After that, the 3D data under each local coordinate of each scan are registered with the global control points. The method overcomes the error accumulation in the traditional registration process and reduces the time consumption of the following 3D data global optimization. The multiview 3D scan registration precision and efficiency are increased. Experiments verify the effectiveness of the proposed algorithm.


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