Search Results - Inverse compositional Gauss–Newton algorithm

Statistical Error Analysis of the Inverse Compositional Gauss-Newton Algorithm in Digital Image Correlation

Authors: Xinxing Shao Xiaoyuan He

Source: International Digital Imaging Correlation Society ISBN: 9788743803133

Access URL: https://link.springer.com/chapter/10.1007/978-3-319-51439-0_18
https://rd.springer.com/chapter/10.1007/978-3-319-51439-0_18

Experimental assessment of noise robustness of the forward-additive, symmetric-additive and the inverse-compositional Gauss-Newton algorithm in digital image correlation

Authors: A. Baldi P. M. Santucci F. Bertolino

Source: Optics and Lasers in Engineering. 154:107012

Subject Terms: 0203 mechanical engineering, 0103 physical sciences, 02 engineering and technology, Digital Image Correlation, Noise bias, Forward-Additive Gauss-Newton algorithm, Inverse-Compositional Gauss-Newton algorithm, 01 natural sciences

File Description: application/pdf

Interpolation bias for the inverse compositional Gauss–Newton algorithm in digital image correlation

Authors: Qingchuan Zhang Xiaohai Xu Shangquan Wu et al.

Source: Optics and Lasers in Engineering. 100:267-278

Subject Terms: 0203 mechanical engineering, 0103 physical sciences, 02 engineering and technology, 01 natural sciences

Access URL: https://ui.adsabs.harvard.edu/abs/2018OptLE.100..267S/abstract
https://www.sciencedirect.com/science/article/pii/S014381661730341X

Noise robustness and parallel computation of the inverse compositional Gauss–Newton algorithm in digital image correlation

Authors: Xiangjun Dai Xinxing Shao Xiaoyuan He

Source: Optics and Lasers in Engineering. 71:9-19

Subject Terms: 0103 physical sciences, 01 natural sciences, 0104 chemical sciences

Access URL: https://www.sciencedirect.com/science/article/pii/S0143816615000445
https://ui.adsabs.harvard.edu/abs/2015OptLE..71....9S/abstract

An Evaluation of Convergence Criteria for Digital Image Correlation Using Inverse Compositional Gauss–Newton Algorithm

Authors: Bing Pan

Source: Strain. 50:48-56

Subject Terms: 0203 mechanical engineering, 0103 physical sciences, 02 engineering and technology, 01 natural sciences

Access URL: https://onlinelibrary.wiley.com/doi/full/10.1111/str.12066
http://onlinelibrary.wiley.com/resolve/doi?DOI=10.1111%2Fstr.12066
https://onlinelibrary.wiley.com/doi/10.1111/str.12066/pdf

Classic and inverse compositional Gauss‐Newton in global DIC

Authors: Jean-Charles Passieux Robin Bouclier Passieux, Jean-Charles et al.

Contributors: Jean-Charles Passieux Robin Bouclier Passieux, Jean-Charles et al.

Source: International Journal for Numerical Methods in Engineering. 119:453-468

Subject Terms: 0203 mechanical engineering, [SPI.MECA.STRU]Engineering Sciences [physics]/Mechanics [physics.med-ph]/Structural mechanics [physics.class-ph], inverse compositional Gauss-Newton, global DIC, forward compositional Gauss-Newton, [SPI.MECA.STRU] Engineering Sciences [physics]/Mechanics [physics.med-ph]/Structural mechanics [physics.class-ph], 02 engineering and technology

File Description: application/pdf

Access URL: https://hal.archives-ouvertes.fr/hal-02059472/file/icgn19_JCP_RB.pdf
http://ui.adsabs.harvard.edu/abs/2019IJNME.119..453P/abstract
https://hal.archives-ouvertes.fr/hal-02059472
https://onlinelibrary.wiley.com/doi/full/10.1002/nme.6057
https://hal.archives-ouvertes.fr/hal-02059472/document
https://hal.science/hal-02059472v1/document
https://doi.org/10.1002/nme.6057
https://hal.science/hal-02059472v1

Optical coherence elastography based on inverse compositional Gauss-Newton digital volume correlation with second-order shape function

Authors: Hao Wu Jiaqiu Wang Jorge Alberto Amaya Catano et al.

Source: Optics Express. 30:41954

Subject Terms: 0103 physical sciences, Elasticity Imaging Techniques, 01 natural sciences, Tomography, Optical Coherence, Algorithms, 0104 chemical sciences

File Description: application/pdf

Access URL: https://pubmed.ncbi.nlm.nih.gov/36366659

Three‐dimensional static optical coherence elastography based on inverse compositional Gauss‐Newton digital volume correlation

Authors: Fanchao Meng Cheng Chen Shun Hui et al.

Source: Journal of Biophotonics. 12

Subject Terms: Models, Statistical, Phantoms, Imaging, Lasers, Reproducibility of Results, 01 natural sciences, Motion, Imaging, Three-Dimensional, Tensile Strength, Calibration, 0103 physical sciences, Image Processing, Computer-Assisted, Animals, Anisotropy, Elasticity Imaging Techniques, Poisson Distribution, Stress, Mechanical, Muscle, Skeletal, Shear Strength, Chickens, Algorithms, Software, Tomography, Optical Coherence

Access URL: https://pubmed.ncbi.nlm.nih.gov/31008547
https://www.onlinelibrary.wiley.com/doi/abs/10.1002/jbio.201800422
https://www.onlinelibrary.wiley.com/doi/epdf/10.1002/jbio.201800422
https://www.ncbi.nlm.nih.gov/pubmed/31008547

An Evaluation of Convergence Criteria for Digital Image Correlation Using Inverse Compositional Gauss-Newton Algorithm.

Authors: Pan, B.

Source: Strain; Feb2014, Vol. 50 Issue 1, p48-56, 9p

Subject Terms: DIGITAL image correlation, STOCHASTIC convergence, GAUSS-Newton method, INVERSE problems, ROBUST control, ITERATIVE methods (Mathematics)

Rationalizing Efficient Compositional Image Alignment: The Constant Jacobian Gauss-Newton Optimization Algorithm

Authors: Luis Baumela Enrique Muñoz Pablo Márquez-Neila

Source: International Journal of Computer Vision. 112:354-372

Subject Terms: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Significance of Parallel Computing on the Performance of Digital Image Correlation Algorithms in MATLAB

Authors: Andreas Thoma Abhijith Moni Sridhar Ravi

Source: Designs, Vol 5, Iss 1, p 15 (2021)

Subject Terms: digital image correlation, real-time processing, Newton–Raphson method, particle swarm optimization, inverse-compositional Gauss–Newton method, parallel computation, Technology, Engineering design, TA174

Relation: https://www.mdpi.com/2411-9660/5/1/15; https://doaj.org/toc/2411-9660; https://doaj.org/article/54a0707c68f349909ce7ca43310f49d1

Availability: https://doi.org/10.3390/designs5010015
https://doaj.org/article/54a0707c68f349909ce7ca43310f49d1

Classic and inverse compositional Gauss‐Newton in global DIC.

Authors: Passieux, Jean‐Charles Bouclier, Robin

Source: International Journal for Numerical Methods in Engineering; 8/10/2019, Vol. 119 Issue 6, p453-468, 16p

Subject Terms: DIGITAL image correlation, GAUSS-Newton method, MATHEMATICAL optimization, LINEAR operators, DEFORMATION of surfaces

Performance of global look-up table strategy in digital image correlation with cubic B-spline interpolation and bicubic interpolation

Authors: Pan, Zhiwei Chen, Wei Jiang, Zhenyu et al.

Source: Theoretical and Applied Mechanics Letters, Vol 6, Iss 3, Pp 126-130 (2016)

Subject Terms: Cubic B-spline interpolation, 0203 mechanical engineering, 13. Climate action, Bicubic interpolation, Global look-up table, 0103 physical sciences, Digital image correlation, 02 engineering and technology, TA1-2040, Engineering (General). Civil engineering (General), 01 natural sciences, 7. Clean energy, Inverse compositional Gauss–Newton algorithm

Access URL: https://doaj.org/article/4b5e4cb242554d119faa4f942a89def3
https://core.ac.uk/display/43726196
https://www.sciencedirect.com/science/article/pii/S2095034916300113
http://www.sciencedirect.com/science/article/pii/S2095034916300113

An improved stereo matching algorithm based on digital image correlation in 3D shape measurement.

Authors: Qian, Boxing Pan, Hanfei Shao, Wei et al.

Source: Measurement Science & Technology; Apr2025, Vol. 36 Issue 4, p1-11, 11p

Subject Terms: DIGITAL image correlation, SHAPE measurement, MATRIX inversion, STANDARD deviations, THREE-dimensional imaging, DIGITAL images

Visual Sensors

Authors: Reinoso Garcia, Oscar Payá, Luis

Subject Terms: orientation relevance, sweet pepper, lane marking reconstruction, convolutional neural network, stereo-vision, single-shot 3D shape measurement, star image prediction, human visual system, support vector machines, motion estimation, patrol robot, mobile robots, iris recognition, motif co-occurrence histogram, advanced driver assistance system (ADAS), sign language, Gray code, appearance-temporal features, depth vision, fused point and line feature matching, robotics, FOV, image mosaic, visible light and near-infrared light camera sensors, illumination, indoor visual SLAM, textile localization, confidence response map, recognition algorithm, SLAM, inverse compositional Gauss-Newton algorithm, planes intersection, support vector machine (SVM), camera pose, TA1-2040, vibration, LSTM, camera calibration, iterative closest point, point cloud, appearance based model, statistical information of gray-levels differences, ego-motion estimation, catadioptric sensor, RGB-D sensor, warp function, texture description, image retrieval, texture retrieval, optical flow, action segmentation, visual odometry, thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology, automatic calibration, digital image correlation, 3D reconstruction, receptive field correspondence, visual detection, visual information fusion, Visual Sensors, semantic mapping, fringe projection profilometry, pedestrian detection, Siamese network, star sensor, visual tracking, lane marking, semantic segmentation, robot manipulation, n/a, end-to-end architecture, sensors combination, hybrid histogram descriptor, Richardson-Lucy algorithm, background dictionary, parallel line, rotation-angle, spatial transformation, human visual attention, scale invariance, action localization, indoor environment, robotic welding, speed measurement, depth image registration, Local Binary Patterns, laser sensor, stereo camera, image binarization, visual mapping, UAV image, underwater imaging, correlation filters, structure extraction, regression based model, dynamic programming, person re-identification, 3D ConvNets, convolutional neural network (CNN), geometric moments, pivotal frames, simplified initialization strategy, checkerboard, RGB-D, map representation, soft decision tree, stereo vision, CLOSIB, finger alphabet, large field of view, salient region detection, omnidirectional imaging, embedded systems, skeletal data, tightly-coupled VIO, Manhattan frame estimation, neural network, consistent line clustering, adaptive update strategy, textile retrieval, seam-line, pose estimation, lane marking detection, object recognition, vision system, presentation attack detection, content-based image retrieval, seam tracking, T1-995, vision-guided robotic grasping, quality control, automated design, GTAW, line scan camera, visual sensors, non-rigid reconstruction, stereo, adaptive model, extrinsic calibration, iris segmentation, calibration, symmetry axis, straight wing aircraft, image processing, around view monitor (AVM) system, motion-aware, handshape recognition, local parallel cross pattern, narrow butt joint, pose estimates, perceptually uniform histogram, LRF, visual sensor, visual localization, boosted decision tree, texture classification, parking assist system, global feature descriptor, measurement error, RGB-D SLAM

File Description: application/octet-stream

Access URL: https://mdpi.com/books/pdfview/book/2141
https://directory.doabooks.org/handle/20.500.12854/62289

Path-independent digital image correlation with high accuracy, speed and robustness

Authors: Jiang, Zhenyu Qian, Kemao Miao, Hong et al.

Contributors: Jiang, Zhenyu Qian, Kemao Miao, Hong et al.

Source: Optics and Lasers in Engineering. 65:93-102

Subject Terms: Gauss–Newton method, Path-independence, 0203 mechanical engineering, Fast Fourier transform, Inverse compositional algorithm, 0103 physical sciences, Digital image correlation, 02 engineering and technology, 01 natural sciences

File Description: application/pdf

Access URL: https://dr.ntu.edu.sg/bitstream/10356/81521/1/Path-independent%20digital%20image%20correlation%20with%20high%20accuracy%2c%20speed%20and%20robustness.pdf
http://repository.ust.hk/ir/Record/1783.1-80101
https://ui.adsabs.harvard.edu/abs/2015OptLE..65...93J/abstract
https://dr.ntu.edu.sg/handle/10356/81521?mode=full
https://dr.ntu.edu.sg/bitstream/10356/81521/1/Path-independent%20digital%20image%20correlation%20with%20high%20accuracy%2c%20speed%20and%20robustness.pdf
http://or.nsfc.gov.cn/bitstream/00001903-5/188807/1/1000009229413.pdf
https://www.sciencedirect.com/science/article/pii/S0143816614001560
http://hdl.handle.net/10220/40826
https://hdl.handle.net/10356/81521

Algorithm Analysis and Optimization of a Digital Image Correlation Method Using a Non-Probability Interval Multidimensional Parallelepiped Model.

Authors: Zhu, Xuedong Liu, Jianhua Ao, Xiaohui et al.

Source: Sensors (14248220); Oct2024, Vol. 24 Issue 19, p6460, 15p

Subject Terms: ALGORITHMS

On the Compositional Step of the IC-GN Digital Image Correlation Algorithm

Authors: Baldi, Antonio Santucci, Pietro Maria

Contributors: Baldi, Antonio Santucci, Pietro Maria

Relation: volume:1306; numberofpages:13; journal:IOP CONFERENCE SERIES: MATERIALS SCIENCE AND ENGINEERING; https://hdl.handle.net/11584/400544

Availability: https://hdl.handle.net/11584/400544
https://doi.org/10.1088/1757-899x/1306/1/012038

Comparative Analysis of Warp Function for Digital Image Correlation-Based Accurate Single-Shot 3D Shape Measurement

Authors: Xiao Yang Xiaobo Chen Juntong Xi

Source: Sensors, Vol 18, Iss 4, p 1208 (2018)

Subject Terms: single-shot 3D shape measurement, digital image correlation, warp function, inverse compositional Gauss-Newton algorithm, Chemical technology, TP1-1185

Relation: http://www.mdpi.com/1424-8220/18/4/1208; https://doaj.org/toc/1424-8220; https://doaj.org/article/50bc0c16989f46429c454d333ad1efe5

Availability: https://doi.org/10.3390/s18041208
https://doaj.org/article/50bc0c16989f46429c454d333ad1efe5

Particle tracking-aided digital volume correlation for clay–sand soil mixtures.

Authors: Wu, Mengmeng Wang, Jianfeng Pan, Bing et al.

Source: Géotechnique; Jun2025, Vol. 75 Issue 6, p760-772, 13p

Subject Terms: COMPUTED tomography, POTTING soils, CLAY soils, SOIL classification, COMPUTER vision