Добірка наукової літератури з теми "Plant 3D reconstruction"
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Статті в журналах з теми "Plant 3D reconstruction"
Ando, Ryuhei, Yuko Ozasa, and Wei Guo. "Robust Surface Reconstruction of Plant Leaves from 3D Point Clouds." Plant Phenomics 2021 (April 2, 2021): 1–15. http://dx.doi.org/10.34133/2021/3184185.
Повний текст джерелаWang, Jizhang, Yun Zhang, and Rongrong Gu. "Research Status and Prospects on Plant Canopy Structure Measurement Using Visual Sensors Based on Three-Dimensional Reconstruction." Agriculture 10, no. 10 (October 8, 2020): 462. http://dx.doi.org/10.3390/agriculture10100462.
Повний текст джерелаYin, Kangxue, Hui Huang, Pinxin Long, Alexei Gaissinski, Minglun Gong, and Andrei Sharf. "Full 3D Plant Reconstruction via Intrusive Acquisition." Computer Graphics Forum 35, no. 1 (August 25, 2015): 272–84. http://dx.doi.org/10.1111/cgf.12724.
Повний текст джерелаYang, Myongkyoon, and Seong-In Cho. "High-Resolution 3D Crop Reconstruction and Automatic Analysis of Phenotyping Index Using Machine Learning." Agriculture 11, no. 10 (October 15, 2021): 1010. http://dx.doi.org/10.3390/agriculture11101010.
Повний текст джерелаSun, Guoxiang, and Xiaochan Wang. "Three-Dimensional Point Cloud Reconstruction and Morphology Measurement Method for Greenhouse Plants Based on the Kinect Sensor Self-Calibration." Agronomy 9, no. 10 (September 28, 2019): 596. http://dx.doi.org/10.3390/agronomy9100596.
Повний текст джерелаHartley, Zane K. J., Aaron S. Jackson, Michael Pound, and Andrew P. French. "GANana: Unsupervised Domain Adaptation for Volumetric Regression of Fruit." Plant Phenomics 2021 (October 8, 2021): 1–11. http://dx.doi.org/10.34133/2021/9874597.
Повний текст джерелаSchunck, David, Federico Magistri, Radu Alexandru Rosu, André Cornelißen, Nived Chebrolu, Stefan Paulus, Jens Léon, et al. "Pheno4D: A spatio-temporal dataset of maize and tomato plant point clouds for phenotyping and advanced plant analysis." PLOS ONE 16, no. 8 (August 18, 2021): e0256340. http://dx.doi.org/10.1371/journal.pone.0256340.
Повний текст джерелаWang, Feiyi, Xiaodan Ma, Meng Liu, and Bingxue Wei. "Three-Dimensional Reconstruction of Soybean Canopy Based on Multivision Technology for Calculation of Phenotypic Traits." Agronomy 12, no. 3 (March 12, 2022): 692. http://dx.doi.org/10.3390/agronomy12030692.
Повний текст джерелаFang, Wei, Hui Feng, Wanneng Yang, Lingfeng Duan, Guoxing Chen, Lizhong Xiong, and Qian Liu. "High-throughput volumetric reconstruction for 3D wheat plant architecture studies." Journal of Innovative Optical Health Sciences 09, no. 05 (July 18, 2016): 1650037. http://dx.doi.org/10.1142/s1793545816500371.
Повний текст джерелаZaman, Sharifa, and B. Fatima. "THREE-DIMENSIONAL RECONSTRUCTION AND VISUALIZATION OF PLANT CELLS." Journal of Mountain Area Research 5 (December 29, 2020): 28. http://dx.doi.org/10.53874/jmar.v5i0.80.
Повний текст джерелаДисертації з теми "Plant 3D reconstruction"
Preuksakarn, Chakkrit. "Reconstructing plant architecture from 3D laser scanner data." Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20116/document.
Повний текст джерелаIn the last decade, very realistic rendering of plant architectures have been produced in computer graphics applications. However, in the context of biology and agronomy, acquisition of accurate models of real plants is still a tedious task and a major bottleneck for the construction of quantitative models of plant development. Recently, 3D laser scanners made it possible to acquire 3D images on which each pixel has an associate depth corresponding to the distance between the scanner and the pinpointed surface of the object. Standard geometrical reconstructions fail on plants structures as they usually contain a complex set of discontinuous or branching surfaces distributed in space with varying orientations. In this thesis, we present a method for reconstructing virtual models of plants from laser scanning of real-world vegetation. Measuring plants with laser scanners produces data with different levels of precision. Points set are usually dense on the surface of the main branches, but only sparsely cover thin branches. The core of our method is to iteratively create the skeletal structure of the plant according to local density of point set. This is achieved thanks to a method that locally adapts to the levels of precision of the data by combining a contraction phase and a local point tracking algorithm. In addition, we present a quantitative evaluation procedure to compare our reconstructions against expertised structures of real plants. For this, we first explore the use of an edit distance between tree graphs. Alternatively, we formalize the comparison as an assignment problem to find the best matching between the two structures and quantify their differences
Schöler, Florian [Verfasser]. "3D Reconstruction of Plant Architecture by Grammar-based Modeling and Markov Chain Sampling / Florian Schöler." Bonn : Universitäts- und Landesbibliothek Bonn, 2014. http://d-nb.info/1060787245/34.
Повний текст джерелаBartoli, Adrien. "Reconstruction et alignement en vision 3D : points, droites, plans et caméras." Phd thesis, Grenoble INPG, 2003. http://tel.archives-ouvertes.fr/tel-00004360.
Повний текст джерелаKarlsson, Anette. "In-Plane Motion Correction in Reconstruction of non-Cartesian 3D-functional MRI." Thesis, Linköpings universitet, Datorseende, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-72056.
Повний текст джерелаNär patienter rör sig under en MRI-undersökning uppstår artefakter i den rekonstruerande bilden och därför är det önskvärt med rörelsekorrigering. En 2D- rörelsekorrigeringsalgoritm som är anpassad för PRESTO-CAN har tagits fram. PRESTO-CAN är en ny fMRI-metod för 3D där samplingen av k-rummet är radiell i (kx,kz)-planet och kartesisk i ky-riktningen. Rotations- och translationsrörelser kan estimeras separat då magnituden av signalen bara påverkas av rotationsrörelser. Eftersom data är samplat radiellt kan rotationen estimeras genom att hitta translationen i vinkelled med hjälp av cirkulär korrelation. Korrelation används även för att hitta translationen i i x- och z-riktningen. Test på simulerat data visar att rörelsekorrigeringsalgoritmen både detekterar och korrigerar för rörelser vilket leder till bilder med mycket mindre rörelseartefakter.
Dosch, Philippe. "Un environnement pour la reconstruction 3D d'édifices à partir de plans d'architecte." Nancy 1, 2000. http://docnum.univ-lorraine.fr/public/SCD_T_2000_0066_DOSCH.pdf.
Повний текст джерелаThis thesis is in line with the field of document analysis, and more precisely deals with graphics recognition. Our purpose is the construction of a 3D model of a building from the architectural drawings of its f1oors. For that, we have a set of analysis modules and a graphical user interface (GUI) allowing a human operator to control the processings to be pelformed in an optimal way. The major part of this thesis describes the various processings implemented, from the low-level (bitmap images processings) to the high-Ievel (vectorized data processings). We describe the choices which have led us to define a threelayered software architecture, hierarchally organized: A library of software components, an applicative layer grouping the various processings together and the GUI. The latter allows to directly interact on data to control the the analysis, and manages the man-machine cooperation. All the members of our research teams have been involved in this work, but our main contributions concem the design of the GUI, the spatial organization of processings (tiling), the extraction of middle-level features (dashed and dotted lines, symbols such as stairwell, etc. ) and matching algorithms to construct the 3D structure of a building, as weil as the software integration and the design of the GUI
Jonsson, Mikael. "Make it Flat : Detection and Correction of Planar Regions in Triangle Meshes." Thesis, Linköpings universitet, Datorseende, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-126589.
Повний текст джерелаKonsten att digitalt rekonstruera en verklig miljö har länge varit intressant för forskare. Nyligen har området även tilldragit sig mer och mer uppmärksamhet från företag som ser en möjlighet att föra den här typen av teknik till produkter på marknaden. I synnerhet är digital rekonstruktion av byggnader en nisch som har både stor potential och möjlighet till förbättring. Med denna bakgrund så presenterar detta examensarbete designen för och utvärderingen av en pipeline som skapats för att detektera och rätta till approximativt platta regioner i arkitektoniska miljöer. Miljöerna är 3D-rekonstruerade triangelmeshar skapade från RGB-bilder. Examensarbetet omfattar även utvärdering av olika komponenter för att uppnå detta, som avslutas med att de mest lämpliga komponenterna presenteras. Målet i korthet är att förbättra den visuella kvaliteten av en rekonstruerad modell. Den slutgiltiga pipelinen består av två övergripande block - ett för att detektera initiala plan och ett för att förbättra de funna planen. Det första blocket använder en multi-label energiformulering på grafen som beskriver den rekonstruerade ytan. Straffvärden tilldelas varje vertex och varje båge i grafen baserade på varje vertex label. På så sätt beskriver grafen ett Markov Random Field. Energin är sedan minimerad med alpha-expansion-algoritmen. Det andra blocket använder heuristiker för att låta planen växa, slå ihop närliggande plan och för att extrahera avvikande detaljer. Resultat på flera miljöer presenteras också för att påvisa att den visuella kvaliteten har förbättrats utan att rekonstruktionens noggrannhet har försämrats jämfört med ground truth-data.
Da, Costa Luis Eduardo. "Reconstruction de modèles 3D à partir d'information 2D partielle : application au cas d'une plante." Mémoire, École de technologie supérieure, 2007. http://espace.etsmtl.ca/573/1/DA_COSTA_Luis_Eduardo.pdf.
Повний текст джерелаHorna, Sébastien. "Reconstruction géométrique et topologique de complexes architecturaux 3D à partir de plans numériques 2D." Poitiers, 2008. http://theses.edel.univ-poitiers.fr/theses/2008/Horna-Sebastien/2008-Horna-Sebastien-These.pdf.
Повний текст джерелаVirtual architectural (indoor) scenes are often modelled in 3D for various types of simulation systems. For instance, some authors propose methods dedicated to lighting, heat transfer, acoustic or radio wave propagation simulations. These methods rely in most cases on a volumetric representation of the environment, with adjacency and incidence relationships. Unfortunately, many buildings data are only given by 2D plans and the 3D needs varies from one application to another. To solve these problems, we propose a formal representation of consistency constraints dedicated to building interiors and associated with a topological model. We show that such a representation can be used for : (i) reconstructing a 3D model from 2D architectural plans ; (ii) detecting automatically geometrical, topological and semantical inconsistencies ; (iii) designing automatic and semi-automatic operations to correct and enrich a 2D plan. All our constraints are homogeneously defined in 2D and 3D, implemented with generalized maps and used in modeling operations. We explain how this model can be successfully used with various ray-tracing methods
Da, Costa Luis Eduardo. "Reconstruction de modèles 3D à partir d'information 2D partielle : application au cas d'une plante /." Thèse, Montréal : École de technologie supérieure, 2007. http://proquest.umi.com/pqdweb?did=1397920901&sid=3&Fmt=2&clientId=46962&RQT=309&VName=PQD.
Повний текст джерела"Thèse présentée à l'École de technologie supérieure comme exigence partielle à l'obtention du doctorat en génie". CaQQUQ Bibliogr. : f. [173]-179. Également disponible en version électronique. CaQMUQET
Bui, Cao Vu. "Modélisation d'environnements intérieurs par reconstruction 3D en temps réel et extraction de plans architecturaux 2D." Thesis, Troyes, 2018. http://www.theses.fr/2018TROY0032.
Повний текст джерелаScene reconstruction is the process of building an accurate geometric model of one's environment from We explore the problem of complete scene reconstruction in indoor environments using mixed - data from the low-cost RGB-D camera and the inertial unit. The scanning process is realized in real-time, on the move with 6DoF of the numerizing system. We focus on computationally-constrained mobile systems, such as smartphone or tablet devices. Problematic issues present a set of fundamental challenges - estimating the state and trajectory of the device as it moves while scanning environment and utilizing lightweight data structures to hold the representation of the reconstructed scene. The system needs to be computationally and memory-efficient, so that it can run in real time, on-board the mobile device. The point-cloud resulted in the above module, which is non-structured and noisy cause of the quality of the low-cost sensor, needed a new method for the surface reconstruction. Our Dodecahedron Mapping is presented like a triangulation solution for the completed indoor environment scanning. After filtering and smoothing the point cloud, the algorithm tries to approximating the surface mesh by deforming and pasting the dodecahedron surface to the scanned point cloud. And the last stage of this research mission is to developing tools for the automatic extraction of 2D architectural plans from the 3D scanned building scene. This extracting process is also possible from the 3D point cloud or mesh by defining a section plane
Частини книг з теми "Plant 3D reconstruction"
Schöler, Florian, and Volker Steinhage. "Towards an Automated 3D Reconstruction of Plant Architecture." In Applications of Graph Transformations with Industrial Relevance, 51–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34176-2_6.
Повний текст джерелаLou, Lu, Yonghuai Liu, Jiwan Han, and John H. Doonan. "Accurate Multi-View Stereo 3D Reconstruction for Cost-Effective Plant Phenotyping." In Lecture Notes in Computer Science, 349–56. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11755-3_39.
Повний текст джерелаGuan, Xin, Jinpeng Wang, Yang Zhou, Kemo Jin, and Nianyu Zou. "Study on 3D Reconstruction of Plant Root Phenotype Based on X-CT Technique." In Green Energy and Networking, 182–92. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62483-5_20.
Повний текст джерелаLivingston III, David P., and Tan Tuong. "3D Reconstruction of Frozen Plant Tissue: A Unique Histological Analysis to Image Postfreeze Responses." In Plant and Microbe Adaptations to Cold in a Changing World, 107–17. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8253-6_9.
Повний текст джерелаHoli, Pavitra, Seong Sill Park, Ashok Kumar Patil, G. Ajay Kumar, and Young Ho Chai. "Intelligent Reconstruction and Assembling of Pipeline from Point Cloud Data in Smart Plant 3D." In Lecture Notes in Computer Science, 360–70. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24078-7_36.
Повний текст джерелаKanatani, Kenichi, Yasuyuki Sugaya, and Yasushi Kanazawa. "3D Reconstruction of a Plane." In Guide to 3D Vision Computation, 107–15. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48493-8_8.
Повний текст джерелаElibol, Armagan, Stefan Posch, Andreas Maurer, Klaus Pillen, and Birgit Möller. "Vision-Based 3D-Reconstruction of Barley Plants." In Pattern Recognition and Image Analysis, 406–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38628-2_48.
Повний текст джерелаPan, Zhigeng, Weixi Hu, Xinyu Guo, and Chunjiang Zhao. "An Efficient Image-Based 3D Reconstruction Algorithm for Plants." In Computational Science and Its Applications – ICCSA 2004, 751–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24709-8_79.
Повний текст джерелаHolzmann, Thomas, Michael Maurer, Friedrich Fraundorfer, and Horst Bischof. "Semantically Aware Urban 3D Reconstruction with Plane-Based Regularization." In Computer Vision – ECCV 2018, 487–503. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01264-9_29.
Повний текст джерелаToyooka, Kiminori, and Byung-Ho Kang. "Reconstructing Plant Cells in 3D by Serial Section Electron Tomography." In Methods in Molecular Biology, 159–70. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-643-6_13.
Повний текст джерелаТези доповідей конференцій з теми "Plant 3D reconstruction"
Lin, Chenhui, Hong Wang, Chengliang Liu, and Liang Gong. "3D reconstruction based plant-monitoring and plant-phenotyping platform." In 2020 3rd World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM). IEEE, 2020. http://dx.doi.org/10.1109/wcmeim52463.2020.00115.
Повний текст джерелаGu, Xiaomeng, Lihong Xu, Dawei Li, and Peng Zhang. "3D reconstruction and visualization of plant leaves." In Sixth International Conference on Graphic and Image Processing (ICGIP 2014), edited by Yulin Wang, Xudong Jiang, and David Zhang. SPIE, 2015. http://dx.doi.org/10.1117/12.2179142.
Повний текст джерелаYing Zheng, Steve Gu, Herbert Edelsbrunner, Carlo Tomasi, and Philip Benfey. "Detailed reconstruction of 3D plant root shape." In 2011 IEEE International Conference on Computer Vision (ICCV). IEEE, 2011. http://dx.doi.org/10.1109/iccv.2011.6126475.
Повний текст джерела"3D RECONSTRUCTION OF PLANT ROOTS FROM MRI IMAGES." In International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003869800240033.
Повний текст джерела"3D Reconstruction of Small Plant From Multiple Views." In 2014 ASABE Annual International Meeting. American Society of Agricultural and Biological Engineers, 2014. http://dx.doi.org/10.13031/aim.20141893190.
Повний текст джерелаRoussel, Johanna, Andreas Fischbach, Siegfried Jahnke, and Hanno Scharr. "3D Surface Reconstruction of Plant Seeds by Volume Carving." In Proceedings of the Computer Vision Problems in Plant Phenotyping Workshop 2015. British Machine Vision Association, 2015. http://dx.doi.org/10.5244/c.29.cvppp.7.
Повний текст джерелаKumar, Pankaj, Jason Connor, and Stan Mikiavcic. "High-throughput 3D reconstruction of plant shoots for phenotyping." In 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV). IEEE, 2014. http://dx.doi.org/10.1109/icarcv.2014.7064306.
Повний текст джерелаZhu, Feiyu, Suresh Thapa, Tiao Gao, Yufeng Ge, Harkamal Walia, and Hongfeng Yu. "3D Reconstruction of Plant Leaves for High-Throughput Phenotyping." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622428.
Повний текст джерела"Processing of serial microscopic images for 3D reconstruction of plant tissues." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-375.
Повний текст джерелаCerutti, Guillaume, Sophie Ribes, Christophe Godin, Carlos Galvan-Ampudia, and Teva Vernoux. "3-d Tessellation of Plant Tissue - A Dual Optimization Approach to Cell-Level Meristem Reconstruction from Microscopy Images." In 2015 International Conference on 3D Vision (3DV). IEEE, 2015. http://dx.doi.org/10.1109/3dv.2015.57.
Повний текст джерела