Academic literature on the topic 'Matching points'
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Journal articles on the topic "Matching points"
Ábrego, Bernardo M., Esther M. Arkin, Silvia Fernández-Merchant, Ferran Hurtado, Mikio Kano, Joseph S. B. Mitchell, and Jorge Urrutia. "Matching Points with Squares." Discrete & Computational Geometry 41, no. 1 (July 3, 2008): 77–95. http://dx.doi.org/10.1007/s00454-008-9099-1.
Full textVincent, Etienne, and Robert Laganière. "Detecting and matching feature points." Journal of Visual Communication and Image Representation 16, no. 1 (February 2005): 38–54. http://dx.doi.org/10.1016/j.jvcir.2004.05.001.
Full textCaraballo, L. E., C. Ochoa, P. Pérez-Lantero, and J. Rojas-Ledesma. "Matching colored points with rectangles." Journal of Combinatorial Optimization 33, no. 2 (October 27, 2015): 403–21. http://dx.doi.org/10.1007/s10878-015-9971-x.
Full textYuan, Wei, Shiyu Chen, Yong Zhang, Jianya Gong, and Ryosuke Shibasaki. "AN AERIAL-IMAGE DENSE MATCHING APPROACH BASED ON OPTICAL FLOW FIELD." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 9, 2016): 543–48. http://dx.doi.org/10.5194/isprsarchives-xli-b3-543-2016.
Full textYuan, Wei, Shiyu Chen, Yong Zhang, Jianya Gong, and Ryosuke Shibasaki. "AN AERIAL-IMAGE DENSE MATCHING APPROACH BASED ON OPTICAL FLOW FIELD." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B3 (June 9, 2016): 543–48. http://dx.doi.org/10.5194/isprs-archives-xli-b3-543-2016.
Full textCui, Haihua, Wenhe Liao, Xiaosheng Cheng, Ning Dai, and Changye Guo. "Flexible point cloud matching method based on three-dimensional image feature points." Advances in Mechanical Engineering 10, no. 9 (September 2018): 168781401879503. http://dx.doi.org/10.1177/1687814018795032.
Full textPiech, Mateusz, Aleksander Smywinski-Pohl, Robert Marcjan, and Leszek Siwik. "Towards Automatic Points of Interest Matching." ISPRS International Journal of Geo-Information 9, no. 5 (May 1, 2020): 291. http://dx.doi.org/10.3390/ijgi9050291.
Full textBereg, Sergey, Nikolaus Mutsanas, and Alexander Wolff. "Matching points with rectangles and squares." Computational Geometry 42, no. 2 (February 2009): 93–108. http://dx.doi.org/10.1016/j.comgeo.2008.05.001.
Full textYuan, Jian Ying, Xian Yong Liu, and Zhi Qiang Qiu. "A Robust Feature Points Matching Algorithm in 3D Optical Measuring System." Advanced Materials Research 383-390 (November 2011): 5193–99. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.5193.
Full textShan, X. J., and P. Tang. "A Robust False Matching Points Detection Method for Remote Sensing Image Registration." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 29, 2015): 699–702. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-699-2015.
Full textDissertations / Theses on the topic "Matching points"
Avdiu, Blerta. "Matching Feature Points in 3D World." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH, Data- och elektroteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-23049.
Full textKlein, Oliver [Verfasser]. "Shape Matching With Reference Points / Oliver Klein." Berlin : Freie Universität Berlin, 2008. http://d-nb.info/1023050862/34.
Full textStanton, Kevin Blythe. "Matching Points to Lines: Sonar-based Localization for the PSUBOT." PDXScholar, 1993. https://pdxscholar.library.pdx.edu/open_access_etds/4630.
Full textLi, Chih-Lin. "Propensity Score Matching in Observational Studies with Multiple Time Points." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1313420291.
Full textMellado, Nicolas. "Analysis of 3D objects at multiple scales : application to shape matching." Thesis, Bordeaux 1, 2012. http://www.theses.fr/2012BOR14685/document.
Full textOver the last decades, the evolution of acquisition techniques yields the generalization of detailed 3D objects, represented as huge point sets composed of millions of vertices. The complexity of the involved data often requires to analyze them for the extraction and characterization of pertinent structures, which are potentially defined at multiple scales. Amongthe wide variety of methods proposed to analyze digital signals, the scale-space analysis istoday a standard for the study of 2D curves and images. However, its adaptation to 3D dataleads to instabilities and requires connectivity information, which is not directly availablewhen dealing with point sets.In this thesis, we present a new multi-scale analysis framework that we call the GrowingLeast Squares (GLS). It consists of a robust local geometric descriptor that can be evaluatedon point sets at multiple scales using an efficient second-order fitting procedure. We proposeto analytically differentiate this descriptor to extract continuously the pertinent structuresin scale-space. We show that this representation and the associated toolbox define an effi-cient way to analyze 3D objects represented as point sets at multiple scales. To this end, we demonstrate its relevance in various application scenarios.A challenging application is the analysis of acquired 3D objects coming from the CulturalHeritage field. In this thesis, we study a real-world dataset composed of the fragments ofthe statues that were surrounding the legendary Alexandria Lighthouse. In particular, wefocus on the problem of fractured object reassembly, consisting of few fragments (up to aboutten), but with missing parts due to erosion or deterioration. We propose a semi-automaticformalism to combine both the archaeologist’s knowledge and the accuracy of geometricmatching algorithms during the reassembly process. We use it to design two systems, andwe show their efficiency in concrete cases
RAVEENDIRAN, JAYANTHAN. "FAST ESTIMATION OF DENSE DISPARITY MAP USING PIVOT POINTS." OpenSIUC, 2013. https://opensiuc.lib.siu.edu/theses/1208.
Full textWang, Jue. "Modeling and Matching of Landmarks for Automation of Mars Rover Localization." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1213192082.
Full textPalomares, Jean-Louis. "Une nouvelle méthode d’appariement de points d’intérêt pour la mise en correspondance d’images." Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20075/document.
Full textThis thesis adresses the issue of image matching for stereoscopic vison applications and image stabilization of video cameras. Methods of mapping are generally based on the use of interest points in the images, i.e. of points which have strong discontinuities in light intensity. We first present a new descriptor of points of interest, obtained by means of an anisotropic rotary filter which delivers at each point of interest a one-dimensional signature based on an intensity gradient. Invariant to rotation by construction, thisdescriptor has very good properties of robustness and discrimination. We then propose a new matching method invariant to Euclidean and affine transformations. This method exploits the correlation of the signatures subject to moderate warping, and defines a distance measure, necesssary for the matching of points. the results obtained on difficult images augur promising extentions to this method
Stefanik, Kevin Vincent. "Sequential Motion Estimation and Refinement for Applications of Real-time Reconstruction from Stereo Vision." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/76802.
Full textMaster of Science
Yang, Liming. "Recalage robuste à base de motifs de points pseudo aléatoires pour la réalité augmentée." Thesis, Ecole centrale de Nantes, 2016. http://www.theses.fr/2016ECDN0025.
Full textRegistration is a very important task in Augmented Reality (AR). It provides the spatial alignment between the real environment and virtual objects. Unlike tracking (which relies on previous frame information), wide baseline localization finds the correct solution from a wide search space, so as to overcome the initialization or tracking failure problems. Nowadays, various wide baseline localization methods have been applied successfully. But for objects with no or little texture, there is still no promising method. One possible solution is to rely on the geometric information, which sometimes does not vary as much as texture or color. This dissertation focuses on new wide baseline localization methods entirely based on geometric information, and more specifically on points. I propose two novel point pattern matching algorithms, RRDM and LGC. Especially, LGC registers 2D or 3D point patterns under any known transformation type and supports multipattern recognitions. It has a linear behavior with respect to the number of points, which allows for real-time tracking. It is applied to multi targets tracking and augmentation, as well as to 3D model registration. A practical method for projector-camera system calibration based on LGC is also proposed. It can be useful for large scale Spatial Augmented Reality (SAR). Besides, I also developed a method to estimate the rotation axis of surface of revolution quickly and precisely on 3D data. It is integrated in a novel framework to reconstruct the surface of revolution on dense SLAM in real-time
Books on the topic "Matching points"
Speziale, Charles G. On the freestream matching condition for stagnation point turbulent flows. Hampton, Va: ICASE, 1989.
Find full textStuart, Casey-Maslen, Clapham Andrew, Giacca Gilles, and Parker Sarah. Art.18 Secretariat. Oxford University Press, 2016. http://dx.doi.org/10.1093/law/9780198723523.003.0022.
Full textMercati, Flavio. Barbour–Bertotti Best Matching. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789475.003.0004.
Full textMercati, Flavio. Best Matching: Technical Details. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789475.003.0005.
Full textInstitute for Computer Applications in Science and Engineering., ed. On the freestream matching condition for stagnation point turbulent flows. Hampton, VA: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1989.
Find full textInternational Commission on Illumination. Technical Committee 1-02 Luminous Efficiency Functions., ed. Spectral luminous efficiency functions based upon brightness matching for monochromatic point sources 2° and 10° fields. Vienna: Central Bureau of the CIE, 1988.
Find full textGoldberg, Abbie E. Open Adoption and Diverse Families. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190692032.001.0001.
Full textWright, A. G. The Photomultiplier Handbook. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199565092.001.0001.
Full textPietroski, Paul M. Massively monadic, potentially plural. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198812722.003.0007.
Full textMercati, Flavio. A derivation of Shape Dynamics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789475.003.0009.
Full textBook chapters on the topic "Matching points"
Aloupis, Greg, Jean Cardinal, Sébastien Collette, Erik D. Demaine, Martin L. Demaine, Muriel Dulieu, Ruy Fabila-Monroy, et al. "Matching Points with Things." In LATIN 2010: Theoretical Informatics, 456–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12200-2_40.
Full textPlatel, B., E. Balmachnova, L. M. J. Florack, and B. M. ter Haar Romeny. "Top-Points as Interest Points for Image Matching." In Computer Vision – ECCV 2006, 418–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11744023_33.
Full textPlatel, B., E. Balmachnova, L. M. J. Florack, F. M. W. Kanters, and B. M. ter Haar Romeny. "Using Top-Points as Interest Points for Image Matching." In Lecture Notes in Computer Science, 211–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11577812_19.
Full textBereg, Sergey, Nikolaus Mutsanas, and Alexander Wolff. "Matching Points with Rectangles and Squares." In SOFSEM 2006: Theory and Practice of Computer Science, 177–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11611257_15.
Full textÁbrego, Bernardo M., Esther M. Arkin, Silvia Fernández-Merchant, Ferran Hurtado, Mikio Kano, Joseph S. B. Mitchell, and Jorge Urrutia. "Matching Points with Circles and Squares." In Discrete and Computational Geometry, 1–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11589440_1.
Full textLucas, Laurent, Céline Loscos, and Yannick Remion. "Feature Points Detection and Image Matching." In 3D Video, 113–35. Hoboken, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118761915.ch6.
Full textCorujo, Josué, David Flores-Peñaloza, Clemens Huemer, Pablo Pérez-Lantero, and Carlos Seara. "Matching Random Colored Points with Rectangles." In WALCOM: Algorithms and Computation, 261–72. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39881-1_22.
Full textWang, Guilian, Joseph Goguen, Young-Kwang Nam, and Kai Lin. "Critical Points for Interactive Schema Matching." In Advanced Web Technologies and Applications, 654–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24655-8_71.
Full textLi, Xiangru, Tan Yang, Yu Lu, and Zhiheng Wang. "A Novel Iterative SIFT Points Matching Method." In Advances in Intelligent Systems and Computing, 623–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54924-3_59.
Full textLakshmi, S., and V. Sankaranarayanan. "Robust Key Points Matching by Ordinal Measure." In Communications in Computer and Information Science, 346–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-27183-0_37.
Full textConference papers on the topic "Matching points"
Yan, Yuanhui, Haiying Xia, Siqi Huang, and Wenjing Xiao. "An improved matching algorithm for feature points matching." In 2014 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, 2014. http://dx.doi.org/10.1109/icspcc.2014.6986201.
Full textBarenbaum, Pablo, Eduardo Bonelli, and Kareem Mohamed. "Pattern Matching and Fixed Points." In PPDP '18: The 20th International Symposium on Principles and Practice of Declarative Programming. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3236950.3236972.
Full textLi, Yuhua, and Jianqiang Sheng. "Feature-Points Based Shape Matching." In 2012 4th International Conference on Digital Home (ICDH). IEEE, 2012. http://dx.doi.org/10.1109/icdh.2012.61.
Full textJun, Sang. "Point pattern relaxation matching with known number of spurious points." In Third International Symposium on Multispectral Image Processing and Pattern Recognition, edited by Hanqing Lu and Tianxu Zhang. SPIE, 2003. http://dx.doi.org/10.1117/12.538940.
Full textBoluk, S. Arda, and M. Fatih Demirci. "Skeleton critical points for shape matching." In 2016 24th Signal Processing and Communication Application Conference (SIU). IEEE, 2016. http://dx.doi.org/10.1109/siu.2016.7495706.
Full textIslam, S., and Zhu Lin. "Matching interest points of an object." In 2005 International Conference on Image Processing. IEEE, 2005. http://dx.doi.org/10.1109/icip.2005.1529765.
Full textMedvedev, Mikhail, and Mikhail Shleymovich. "Image Key Points Detection and Matching." In Spring/Summer Young Researchers' Colloquium on Software Engineering. Institute for System Programming of the Russian Academy of Sciences, 2013. http://dx.doi.org/10.15514/syrcose-2013-7-26.
Full textMarques, Manuel, and Joao Costeira. "Lamp: Linear approach for matching points." In 2009 16th IEEE International Conference on Image Processing (ICIP 2009). IEEE, 2009. http://dx.doi.org/10.1109/icip.2009.5414238.
Full textQin, Yanyan, Hongke Xu, and Huiru Chen. "Image feature points matching via improved ORB." In 2014 International Conference on Progress in Informatics and Computing (PIC). IEEE, 2014. http://dx.doi.org/10.1109/pic.2014.6972325.
Full textWu, Hua, Zhan Song, Jian Yao, Liang Li, and Yu Gu. "Stereo matching based on support points propagation." In 2012 IEEE International Conference on Information Science and Technology (ICIST). IEEE, 2012. http://dx.doi.org/10.1109/icist.2012.6221743.
Full textReports on the topic "Matching points"
Stanton, Kevin. Matching Points to Lines: Sonar-based Localization for the PSUBOT. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.6514.
Full textFunch, Michael, and Anna Lundgren. Matching the missing links – Skills development in Nordic regions. Nordregio, December 2020. http://dx.doi.org/10.6027/pb2020:8.2001-3876.
Full textDow, Stephen J. EPBST Workstation Improvement: Automated Point Matching. Fort Belvoir, VA: Defense Technical Information Center, November 2001. http://dx.doi.org/10.21236/ada397028.
Full textHopcroft, John E., and Daniel P. Huttenlocher. On Planar Point Matching under Affine Transformation. Fort Belvoir, VA: Defense Technical Information Center, April 1989. http://dx.doi.org/10.21236/ada210106.
Full textZheng, Yefeng, and David Doermann. Robust Point Matching for Non-Rigid Shapes: A Relaxation Labeling Based Approach. Fort Belvoir, VA: Defense Technical Information Center, December 2004. http://dx.doi.org/10.21236/ada453579.
Full textMcPhedran, R., K. Patel, B. Toombs, P. Menon, M. Patel, J. Disson, K. Porter, A. John, and A. Rayner. Food allergen communication in businesses feasibility trial. Food Standards Agency, March 2021. http://dx.doi.org/10.46756/sci.fsa.tpf160.
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