Relevant bibliographies by topics / Geometric fitting

Academic literature on the topic 'Geometric fitting'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Geometric fitting"

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Martínez-Morales, José L. "Geometric data fitting." Abstract and Applied Analysis 2004, no. 10 (2004): 831–80. http://dx.doi.org/10.1155/s1085337504401043.

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Xiao, Guobao, Hanzi Wang, Taotao Lai, and David Suter. "Hypergraph modelling for geometric model fitting." Pattern Recognition 60 (December 2016): 748–60. http://dx.doi.org/10.1016/j.patcog.2016.06.026.

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Isack, Hossam, and Yuri Boykov. "Energy-Based Geometric Multi-model Fitting." International Journal of Computer Vision 97, no. 2 (July 12, 2011): 123–47. http://dx.doi.org/10.1007/s11263-011-0474-7.

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Wang, Tao, Zhaoyao Shi, and Bo Yu. "A parameterized geometric fitting method for ellipse." Pattern Recognition 116 (August 2021): 107934. http://dx.doi.org/10.1016/j.patcog.2021.107934.

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Ahn, Sung-Joon. "Geometric Fitting of Parametric Curves and Surfaces." Journal of Information Processing Systems 4, no. 4 (December 31, 2008): 153–58. http://dx.doi.org/10.3745/jips.2008.4.4.153.

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Kanatani, Kenichi, Prasanna Rangarajan, Yasuyuki Sugaya, and Hirotaka Niitsuma. "HyperLS for Parameter Estimation in Geometric Fitting." IPSJ Transactions on Computer Vision and Applications 3 (2011): 80–94. http://dx.doi.org/10.2197/ipsjtcva.3.80.

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Chan, T. O., and D. D. Lichti. "3D CATENARY CURVE FITTING FOR GEOMETRIC CALIBRATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII-5/W12 (September 5, 2012): 259–64. http://dx.doi.org/10.5194/isprsarchives-xxxviii-5-w12-259-2011.

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Pham, Trung Thanh, Tat-Jun Chin, Konrad Schindler, and David Suter. "Interacting Geometric Priors For Robust Multimodel Fitting." IEEE Transactions on Image Processing 23, no. 10 (October 2014): 4601–10. http://dx.doi.org/10.1109/tip.2014.2346025.

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Akar, Nail. "Fitting Matrix Geometric Distributions by Model Reduction." Stochastic Models 31, no. 2 (April 3, 2015): 292–315. http://dx.doi.org/10.1080/15326349.2014.1003271.

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Song, Peng, Zhongqi Fu, and Ligang Liu. "Grasp planning via hand-object geometric fitting." Visual Computer 34, no. 2 (November 7, 2016): 257–70. http://dx.doi.org/10.1007/s00371-016-1333-x.

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Dissertations / Theses on the topic "Geometric fitting"

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Martínez-Morales, José L. "Geometric data fitting /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/5819.

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Grönwall, Christina. "Ground object recognition using laser radar data : geometric fitting, performance analysis, and applications /." Linköping : Department of Electrical Engineering, Linköping University, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7582.

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Grönwall, Christna. "Ground Object Recognition using Laser Radar Data : Geometric Fitting, Performance Analysis, and Applications." Doctoral thesis, Linköpings universitet, Institutionen för systemteknik, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-7685.

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This thesis concerns detection and recognition of ground object using data from laser radar systems. Typical ground objects are vehicles and land mines. For these objects, the orientation and articulation are unknown. The objects are placed in natural or urban areas where the background is unstructured and complex. The performance of laser radar systems is analyzed, to achieve models of the uncertainties in laser radar data. A ground object recognition method is presented. It handles general, noisy 3D point cloud data. The approach is based on the fact that man-made objects on a large scale can be considered be of rectangular shape or can be decomposed to a set of rectangles. Several approaches to rectangle fitting are presented and evaluated in Monte Carlo simulations. There are error-in-variables present and thus, geometric fitting is used. The objects can have parts that are subject to articulation. A modular least squares method with outlier rejection, that can handle articulated objects, is proposed. This method falls within the iterative closest point framework. Recognition when several similar models are available is discussed. The recognition method is applied in a query-based multi-sensor system. The system covers the process from sensor data to the user interface, i.e., from low level image processing to high level situation analysis. In object detection and recognition based on laser radar data, the range value’s accuracy is important. A general direct-detection laser radar system applicable for hard-target measurements is modeled. Three time-of-flight estimation algorithms are analyzed; peak detection, constant fraction detection, and matched filter. The statistical distribution of uncertainties in time-of-flight range estimations is determined. The detection performance for various shape conditions and signal-tonoise ratios are analyzed. Those results are used to model the properties of the range estimation error. The detector’s performances are compared with the Cramér-Rao lower bound. The performance of a tool for synthetic generation of scanning laser radar data is evaluated. In the measurement system model, it is possible to add several design parameters, which makes it possible to test an estimation scheme under different types of system design. A parametric method, based on measurement error regression, that estimates an object’s size and orientation is described. Validations of both the measurement system model and the measurement error model, with respect to the Cramér-Rao lower bound, are presented.
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Leung, Nim Keung. "Convexity-Preserving Scattered Data Interpolation." Thesis, University of North Texas, 1995. https://digital.library.unt.edu/ark:/67531/metadc277609/.

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Surface fitting methods play an important role in many scientific fields as well as in computer aided geometric design. The problem treated here is that of constructing a smooth surface that interpolates data values associated with scattered nodes in the plane. The data is said to be convex if there exists a convex interpolant. The problem of convexity-preserving interpolation is to determine if the data is convex, and construct a convex interpolant if it exists.
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Miyawaki, Shinjiro. "Automatic construction and meshing of multiscale image-based human airway models for simulations of aerosol delivery." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/1990.

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The author developed a computational framework for the study of the correlation between airway morphology and aerosol deposition based on a population of human subjects. The major improvement on the previous framework, which consists of a geometric airway model, a computational fluid dynamics (CFD) model, and a particle tracking algorithm, lies in automatic geometry construction and mesh generation of airways, which is essential for a population-based study. The new geometric model overcomes the shortcomings of both centerline (CL)-based cylindrical models, which are based on the skeleton and average branch diameters of airways called one-dimensional (1-D) trees, and computed tomography (CT)-based models. CL-based models are efficient in terms of pre- and post-processing, but fail to represent trifurcations and local morphology. In contrast, in spite of the accuracy of CT-based models, it is time-consuming to build these models manually, and non-trivial to match 1-D trees and three-dimensional (3-D) geometry. The new model, also known as a hybrid CL-CT-based model, is able to construct a physiologically-consistent laryngeal geometry, represent trifurcations, fit cylindrical branches to CT data, and create the optimal CFD mesh in an automatic fashion. The hybrid airway geometries constructed for 8 healthy and 16 severe asthmatic (SA) subjects agreed well with their CT-based counterparts. Furthermore, the prediction of aerosol deposition in a healthy subject by the hybrid model agreed well with that by the CT-based model. To demonstrate the potential application of the hybrid model to investigating the correlation between skeleton structure and aerosol deposition, the author applied the large eddy simulation (LES)-based CFD model that accounts for the turbulent laryngeal jet to three hybrid models of SA subjects. The correlation between diseased branch and aerosol deposition was significant in one of the three SA subjects. However, whether skeleton structure contributes to airway abnormality requires further investigation.
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Mamic, G. J. "Representation and recognition of 3-D free-form objects incorporating statistical techniques." Thesis, Queensland University of Technology, 2002.

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Myles, Ashish. "Linear programming approach to fitting splines through 3D channels." [Gainesville, Fla.] : University of Florida, 2004. http://purl.fcla.edu/fcla/etd/UFE0006260.

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Kříž, Radim. "Uniform Marker Field na válci." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236201.

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This work presents a new extension for Uniform Marker Field, which is able to detect UMF on the cylinder. First part of the text deals with Augmented reality and focuses on systems using markers. It discusses the actual state-of-the-art systems and its possibilities. After that it focuses more deeply on the marker system Uniform marker field and its grayscale variants. Next part of the work describes properties of the cylinder projected in real space. Important properties for detecting are discussed in detail. Then the proposal and description of detection algorithm is presented. Implementation of algorithm is tested and evaluated on the very end of this thesis.
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Pereira, César Augusto Souto. "Estudo da distribuição de tensões em "channel fittings" pelo método dos elementos finitos." Instituto Tecnológico de Aeronáutica, 2004. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=561.

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A estrutura de uma aeronave ée composta de muitas partes, que devem ser unidas para formar sub-partes. Entre muitas opções, "channel fittings" são amplamente utilizados na conexão da asa com a fuselagem do avião. Esse trabalho aplica o método de elementos finitos na modelagem de um "channel fitting", com o propósito principal de avaliação da distribuição de tensões de acordo com a alteração de alguns parâmetros geométricos. Quatro modelos são construídos e apresentados. Os resultados mostram uma sensibilidade importante dos níveis de tensão de acordo com a posição do furo de conexão com o parafuso. Este trabalho também propõe e descreve um procedimento iterativo que permite a aplicação mais precisa de condições de contorno na zona de contato do "fitting" com estrutura de ligação.
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Allavarapu, Santosh. "A New Additive Manufacturing (AM) File Format Using Bezier Patches." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1385114646.

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Books on the topic "Geometric fitting"

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Cheatwood, F. McNeil. An interactive user-friendly approach to surface-fitting three-dimensional geometries. Hampton, Va: Langley Research Center, 1988.

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service), SpringerLink (Online, ed. L1-Norm and L∞-Norm Estimation: An Introduction to the Least Absolute Residuals, the Minimax Absolute Residual and Related Fitting Procedures. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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R, DeJarnette Fred, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., eds. An interactive user-friendly approach to surface-fitting three-dimensional geometries. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Division, 1988.

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R, DeJarnette Fred, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., eds. An interactive user-friendly approach to surface-fitting three-dimensional geometries. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Division, 1988.

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Circular And Linear Regression Fitting Circles And Lines By Least Squares. CRC Press, 2010.

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L1norm And L8norm Estimation An Introduction To The Least Absolute Residuals The Minimax Absolute Residual And Related Fitting Procedures. Springer-Verlag Berlin and Heidelberg GmbH &, 2013.

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Analysis and Design of Univariate Subdivision Schemes Geometry and Computing. Springer, 2010.

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Book chapters on the topic "Geometric fitting"

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Kanatani, Kenichi, Yasuyuki Sugaya, and Yasushi Kanazawa. "Geometric Fitting." In Ellipse Fitting for Computer Vision, 19–29. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-031-01815-2_3.

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Hagen, H., and A. Nawotki. "Variational Design and Parameter Optimized Surface Fitting." In Geometric Modelling, 121–34. Vienna: Springer Vienna, 1998. http://dx.doi.org/10.1007/978-3-7091-6444-0_10.

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Hermann, Thomas, Zoltán Kovács, and Tamás Várady. "Special Applications in Surface Fitting." In Geometric Modeling: Theory and Practice, 14–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60607-6_2.

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Woodford, Oliver J., Minh-Tri Pham, Atsuto Maki, Riccardo Gherardi, Frank Perbet, and Björn Stenger. "Contraction Moves for Geometric Model Fitting." In Computer Vision – ECCV 2012, 181–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33786-4_14.

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Hahmann, S., G. P. Bonneau, and R. Taleb. "Localizing the 4-Split Method for G1 Free-Form Surface Fitting." In Geometric Modelling, 185–98. Vienna: Springer Vienna, 2001. http://dx.doi.org/10.1007/978-3-7091-6270-5_10.

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Kleinsteuber, Martin, and Knut Hüper. "Approximate Geometric Ellipsoid Fitting: A CG-Approach." In Recent Advances in Optimization and its Applications in Engineering, 73–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12598-0_7.

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Hildenbrand, Dietmar. "Fitting of Planes or Spheres to Sets of Points." In Foundations of Geometric Algebra Computing, 61–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31794-1_5.

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Azhar, Faisal, and Stephen Pollard. "Pseudo-geometric Formulation for Fitting Equidistant Parallel Lines." In Computer Vision – ECCV 2016, 600–614. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46478-7_37.

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Hagen, Hans, Siegfried Heinz, and Alexa Nawotki. "Variational Design with Boundary Conditions and Parameter Optimized Surface Fitting." In Geometric Modeling: Theory and Practice, 3–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60607-6_1.

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Rouhani, Mohammad, and Angel D. Sappa. "A Novel Approach to Geometric Fitting of Implicit Quadrics." In Advanced Concepts for Intelligent Vision Systems, 121–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04697-1_12.

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Conference papers on the topic "Geometric fitting"

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Li, Duanshun, and Chen Feng. "Primitive Fitting Using Deep Geometric Segmentation." In 36th International Symposium on Automation and Robotics in Construction. International Association for Automation and Robotics in Construction (IAARC), 2019. http://dx.doi.org/10.22260/isarc2019/0105.

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Xiao, Fan, Guobao Xiao, Yan Yan, Xing Wang, and Hanzi Wang. "Induced subgraph searching for geometric model fitting." In LIDAR Imaging Detection and Target Recognition 2017, edited by Yueguang Lv, Jianzhong Su, Wei Gong, Jian Yang, Weimin Bao, Weibiao Chen, Zelin Shi, Jindong Fei, Shensheng Han, and Weiqi Jin. SPIE, 2017. http://dx.doi.org/10.1117/12.2296331.

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Weiyin Ma and Nailiang Zhao. "Catmull-Clark surface fitting for reverse engineering applications." In Proceedings Geometric Modeling and Processing 2000. Theory and Applications. IEEE, 2000. http://dx.doi.org/10.1109/gmap.2000.838259.

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Zhou, Xiong, Yan Yan, Hanzi Wang, Guobao Xiao, and Rui Wang. "Evolution-based outlier removal for geometric model fitting." In LIDAR Imaging Detection and Target Recognition 2017, edited by Yueguang Lv, Jianzhong Su, Wei Gong, Jian Yang, Weimin Bao, Weibiao Chen, Zelin Shi, Jindong Fei, Shensheng Han, and Weiqi Jin. SPIE, 2017. http://dx.doi.org/10.1117/12.2294000.

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Trung Thanh Pham, Tat-Jun Chin, Jin Yu, and D. Suter. "The Random Cluster Model for robust geometric fitting." In 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2012. http://dx.doi.org/10.1109/cvpr.2012.6247740.

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Ask, Erik, Olof Enqvist, and Fredrik Kahl. "Optimal Geometric Fitting under the Truncated L2-Norm." In 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2013. http://dx.doi.org/10.1109/cvpr.2013.225.

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Tsao, Heng-Chuan, Jyun-Yuan Chen, and Chao-Hung Lin. "Airborne LiDAR point cloud fitting with geometric constraints." In IGARSS 2015 - 2015 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2015. http://dx.doi.org/10.1109/igarss.2015.7325889.

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Groenwall, Christina A., and Mille C. Millnert. "Vehicle size and orientation estimation using geometric fitting." In Aerospace/Defense Sensing, Simulation, and Controls, edited by Firooz A. Sadjadi. SPIE, 2001. http://dx.doi.org/10.1117/12.445401.

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Wong, Hoi Sim, Tat-Jun Chin, Jin Yu, and David Suter. "Dynamic and hierarchical multi-structure geometric model fitting." In 2011 IEEE International Conference on Computer Vision (ICCV). IEEE, 2011. http://dx.doi.org/10.1109/iccv.2011.6126350.

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Tóth, Tekla, and Levente Hajder. "Robust Fitting of Geometric Primitives on LiDAR Data." In 14th International Conference on Computer Vision Theory and Applications. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007572606220629.

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Reports on the topic "Geometric fitting"

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Hopp, Theodore H. Representation of axes for geometric fitting. Gaithersburg, MD: National Institute of Standards and Technology, 1996. http://dx.doi.org/10.6028/nist.ir.5897.

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