Comparative Analysis of Warp Function for Digital Image Correlation-Based Accurate Single-Shot 3D Shape Measurement
Digital image correlation (DIC)-based stereo 3D shape measurement is a kind of single-shot method, which can achieve high precision and is robust to vibration as well as environment noise. The efficiency of DIC has been greatly improved with the proposal of inverse compositional Gauss-Newton (IC-GN)...
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| Vydané v: | Sensors (Basel, Switzerland) Ročník 18; číslo 4; s. 1208 |
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| Abstract | Digital image correlation (DIC)-based stereo 3D shape measurement is a kind of single-shot method, which can achieve high precision and is robust to vibration as well as environment noise. The efficiency of DIC has been greatly improved with the proposal of inverse compositional Gauss-Newton (IC-GN) operators for both first-order and second-order warp functions. Without the algorithm itself, both the registration accuracy and efficiency of DIC-based stereo matching for shapes with different complexities are closely related to the selection of warp function, subset size, and convergence criteria. Understanding the similarity and difference of the impacts of prescribed subset size and convergence criteria on first-order and second-order warp functions, and how to choose a proper warp function and set optimal subset size as well as convergence criteria for different shapes are fundamental problems in realizing efficient and accurate 3D shape measurement. In this work, we present a comparative analysis of first-order and second-order warp functions for DIC-based 3D shape measurement using IC-GN algorithm. The effects of subset size and convergence criteria of first-order and second-order warp functions on the accuracy and efficiency of DIC are comparatively examined with both simulation tests and real experiments. Reference standards for the selection of warp function for different kinds of 3D shape measurement and the setting of proper convergence criteria are recommended. The effects of subset size on the measuring precision using different warp functions are also concluded. |
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| AbstractList | Digital image correlation (DIC)-based stereo 3D shape measurement is a kind of single-shot method, which can achieve high precision and is robust to vibration as well as environment noise. The efficiency of DIC has been greatly improved with the proposal of inverse compositional Gauss-Newton (IC-GN) operators for both first-order and second-order warp functions. Without the algorithm itself, both the registration accuracy and efficiency of DIC-based stereo matching for shapes with different complexities are closely related to the selection of warp function, subset size, and convergence criteria. Understanding the similarity and difference of the impacts of prescribed subset size and convergence criteria on first-order and second-order warp functions, and how to choose a proper warp function and set optimal subset size as well as convergence criteria for different shapes are fundamental problems in realizing efficient and accurate 3D shape measurement. In this work, we present a comparative analysis of first-order and second-order warp functions for DIC-based 3D shape measurement using IC-GN algorithm. The effects of subset size and convergence criteria of first-order and second-order warp functions on the accuracy and efficiency of DIC are comparatively examined with both simulation tests and real experiments. Reference standards for the selection of warp function for different kinds of 3D shape measurement and the setting of proper convergence criteria are recommended. The effects of subset size on the measuring precision using different warp functions are also concluded. Digital image correlation (DIC)-based stereo 3D shape measurement is a kind of single-shot method, which can achieve high precision and is robust to vibration as well as environment noise. The efficiency of DIC has been greatly improved with the proposal of inverse compositional Gauss-Newton (IC-GN) operators for both first-order and second-order warp functions. Without the algorithm itself, both the registration accuracy and efficiency of DIC-based stereo matching for shapes with different complexities are closely related to the selection of warp function, subset size, and convergence criteria. Understanding the similarity and difference of the impacts of prescribed subset size and convergence criteria on first-order and second-order warp functions, and how to choose a proper warp function and set optimal subset size as well as convergence criteria for different shapes are fundamental problems in realizing efficient and accurate 3D shape measurement. In this work, we present a comparative analysis of first-order and second-order warp functions for DIC-based 3D shape measurement using IC-GN algorithm. The effects of subset size and convergence criteria of first-order and second-order warp functions on the accuracy and efficiency of DIC are comparatively examined with both simulation tests and real experiments. Reference standards for the selection of warp function for different kinds of 3D shape measurement and the setting of proper convergence criteria are recommended. The effects of subset size on the measuring precision using different warp functions are also concluded.Digital image correlation (DIC)-based stereo 3D shape measurement is a kind of single-shot method, which can achieve high precision and is robust to vibration as well as environment noise. The efficiency of DIC has been greatly improved with the proposal of inverse compositional Gauss-Newton (IC-GN) operators for both first-order and second-order warp functions. Without the algorithm itself, both the registration accuracy and efficiency of DIC-based stereo matching for shapes with different complexities are closely related to the selection of warp function, subset size, and convergence criteria. Understanding the similarity and difference of the impacts of prescribed subset size and convergence criteria on first-order and second-order warp functions, and how to choose a proper warp function and set optimal subset size as well as convergence criteria for different shapes are fundamental problems in realizing efficient and accurate 3D shape measurement. In this work, we present a comparative analysis of first-order and second-order warp functions for DIC-based 3D shape measurement using IC-GN algorithm. The effects of subset size and convergence criteria of first-order and second-order warp functions on the accuracy and efficiency of DIC are comparatively examined with both simulation tests and real experiments. Reference standards for the selection of warp function for different kinds of 3D shape measurement and the setting of proper convergence criteria are recommended. The effects of subset size on the measuring precision using different warp functions are also concluded. |
| Author | Xi, Juntong Chen, Xiaobo Yang, Xiao |
| AuthorAffiliation | 3 State Key Laboratory of Mechanical System and Vibration, Shanghai 200240, China 2 Shanghai Key Laboratory of Advanced Manufacturing Environment, Shanghai 200030, China 1 School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China; yangxiao1992@sjtu.edu.cn (X.Y.); xiaoboc@sjtu.edu.cn (X.C.) |
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| Author_xml | – sequence: 1 givenname: Xiao orcidid: 0000-0003-4558-8947 surname: Yang fullname: Yang, Xiao – sequence: 2 givenname: Xiaobo surname: Chen fullname: Chen, Xiaobo – sequence: 3 givenname: Juntong surname: Xi fullname: Xi, Juntong |
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| Title | Comparative Analysis of Warp Function for Digital Image Correlation-Based Accurate Single-Shot 3D Shape Measurement |
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