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Статті в журналах з теми "Plant 3D modeling"
Chang, Wushuai, Weiliang Wen, Chenxi Zheng, Xianju Lu, Bo Chen, Ruiqi Li, and Xinyu Guo. "Geometric Wheat Modeling and Quantitative Plant Architecture Analysis Using Three-Dimensional Phytomers." Plants 12, no. 3 (January 18, 2023): 445. http://dx.doi.org/10.3390/plants12030445.
Повний текст джерелаTian, Chun Yao, and Guo You Li. "A Virtual Reality Based 3D Simulation Modeling of Ethylene Cracking Plant." Advanced Materials Research 765-767 (September 2013): 3110–14. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.3110.
Повний текст джерелаWen, Weiliang, Xinyu Guo, Yongjian Wang, Chunjiang Zhao, and Weihua Liao. "Constructing a Three-Dimensional Resource Database of Plants Using Measured in situ Morphological Data." Applied Engineering in Agriculture 33, no. 6 (2017): 747–56. http://dx.doi.org/10.13031/aea.12135.
Повний текст джерелаYin, Mu Yi, Ling Zhang, Wei Li, and Yu Lin Chen. "Research on Virtual Plant Modeling Based on Local Environment Sensitivity." Applied Mechanics and Materials 347-350 (August 2013): 3133–37. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.3133.
Повний текст джерелаDoan, Thien Minh, Khoi Nguyen Nguyen Tran, Tuan Dinh Le, Cang Trong Vo, and Chung Quang Dinh. "SHIP ASSEMBLY DESIGN BY 3D MODELING." Science and Technology Development Journal 14, no. 4 (December 30, 2011): 53–64. http://dx.doi.org/10.32508/stdj.v14i4.2007.
Повний текст джерелаMartinez-Guanter, Jorge, Ángela Ribeiro, Gerassimos G. Peteinatos, Manuel Pérez-Ruiz, Roland Gerhards, José María Bengochea-Guevara, Jannis Machleb, and Dionisio Andújar. "Low-Cost Three-Dimensional Modeling of Crop Plants." Sensors 19, no. 13 (June 28, 2019): 2883. http://dx.doi.org/10.3390/s19132883.
Повний текст джерелаZivkovic, Miroslav, Snezana Vulovic, and Rodoljub Vujanac. "Assessment of the drum remaining lifetime in thermal power plant." Thermal Science 14, suppl. (2010): 313–21. http://dx.doi.org/10.2298/tsci100507030z.
Повний текст джерелаChen, Fang Yi, Tian En Chen, Wei Wang, and Xiao Jing Ma. "A Method of Pepper Plant Modeling and Animation Set-Up in Autodesk Maya." Applied Mechanics and Materials 462-463 (November 2013): 1110–17. http://dx.doi.org/10.4028/www.scientific.net/amm.462-463.1110.
Повний текст джерелаLu, Shenglian, Xinyu Guo, Chunjiang Zhao, and Changfeng Li. "Physical Model for Interactive Deformation of 3D Plant." International Journal of Virtual Reality 10, no. 2 (January 1, 2011): 33–38. http://dx.doi.org/10.20870/ijvr.2011.10.2.2809.
Повний текст джерелаYang, Yubin, Livia Paleari, Lloyd T. Wilson, Roberto Confalonieri, Adriano Z. Astaldi, Mirko Buratti, Zongbu Yan, Eric Christensen, Jing Wang, and Stanley Omar P. B. Samonte. "Characterizing Genotype-Specific Rice Architectural Traits Using Smart Mobile App and Data Modeling." Agronomy 11, no. 12 (November 28, 2021): 2428. http://dx.doi.org/10.3390/agronomy11122428.
Повний текст джерелаДисертації з теми "Plant 3D modeling"
An, Nan. "Plant high-throughput phenotyping using photogrammetry and 3D modeling techniques." Diss., Kansas State University, 2015. http://hdl.handle.net/2097/20493.
Повний текст джерелаAgronomy
Kevin Price
Stephen M. Welch
Plant phenotyping has been studied for decades for understanding the relationship between plant genotype, phenotype, and the surrounding environment. Improved accuracy and efficiency in plant phenotyping is a critical factor in expediting plant breeding and the selection process. In the past, plant phenotypic traits were extracted using invasive and destructive sampling methods and manual measurements, which were time-consuming, labor-intensive, and cost-inefficient. More importantly, the accuracy and consistency of manual methods can be highly variable. In recent years, however, photogrammetry and 3D modeling techniques have been introduced to extract plant phenotypic traits, but no cost-efficient methods using these two techniques have yet been developed for large-scale plant phenotyping studies. High-throughput 3D modeling techniques in plant biology and agriculture are still in the developmental stages, but it is believed that the temporal and spatial resolutions of these systems are well matched to many plant phenotyping needs. Such technology can be used to help rapid phenotypic trait extraction aid crop genotype selection, leading to improvements in crop yield. In this study, we introduce an automated high-throughput phenotyping pipeline using affordable imaging systems, image processing, and 3D reconstruction algorithms to build 2D mosaicked orthophotos and 3D plant models. Chamber-based and ground-level field implementations can be used to measure phenotypic traits such as leaf length, rosette area in 2D and 3D, plant nastic movement, and diurnal cycles. Our automated pipeline has cross-platform capabilities and a degree of instrument independence, making it suitable for various situations.
Balduzzi, Mathilde. "Plant canopy modeling from Terrestrial LiDAR System distance and intensity data." Thesis, Montpellier 2, 2014. http://www.theses.fr/2014MON20203.
Повний текст джерелаThe challenge of this thesis is reconstruct the 3D geometry of vegetation from distance and intensity data provided by a 3D scanner LiDAR. A method of “Shape-From-Shading” by propagation is developed to be combined with a fusion method of type “Kalman” to get an optimal reconstruction of the leaves. -Introduction-The LiDAR data analysis shows that the point cloud quality is variable. This quality depends upon the measurement set up. When the LiDAR laser beam reaches the edge of a surface (or a steeply inclined surface), it also integrate background measurement. Those set up produce outliers. This kind of set up is common for foliage measurement as foliages have in general fragmented and complex shape. LiDAR data are of bad quality and the quantity of leaves in a scan makes the correction of outliers fastidious. This thesis goal is to develop a methodology to allow us to integrate the LiDAR intensity data to the distance to make an automatic correction of those outliers. -Shape-from-shading-The Shape-from-shading principle is to reconstruct the distance values from intensities of a photographed object. The camera (LiDAR sensor) and the light source (LiDAR laser) have the same direction and are placed at infinity relatively to the surface. This makes the distance effect on intensity negligible and the hypothesis of an orthographic camera valid. In addition, the relationship between the incident angle light beam and intensity is known. Thanks to the LiDAR data analysis, we are able to choose the best data between distance and intensity in the scope of leaves reconstruction. An algorithm of propagation SFS along iso-intense regions is developed. This type of algorithm allows us to integrate a fusion method of type Kalman. -Mathematical design of the method-The patches of the surface corresponding to the iso-intense regions are patches of surfaces called the constant slope surfaces, or sand-pile surfaces. We are going to use those surfaces to rebuild the 3D geometry corresponding to the scanned surfaces. We show that from the knowledge of the 3d of an iso-intensity region, we can construct those sand-pile surfaces. The initialization of the first iso-intense regions contour (propagation seeds) is done with the 3D LiDAR data. The greatest slope lines of those surfaces are generated. Thanks to the propagation of those lines (and thus of the corresponding sand-pile surface), we build the other contour of the iso-intense region. Then, we propagate the reconstruction iteratively. -Kalman filter-We can consider this propagation as being the computation of a trajectory on the reconstructed surface. In our study framework, the distance data is always available (3D scanner data). It is thus possible to choose which data (intensity vs distance) is the best to reconstruct the object surface. This can be done with a fusion of type Kalman filter. -Algorithm-To proceed a reconstruction by propagation, it is necessary to order the iso-intensity regions. Once the propagation seeds are found, they are initialized with the distances provided by the LiDAR. For each nodes of the hierarchy (corresponding to an iso-intensity region), the sand-pile surface reconstruction is done. -Manuscript-The thesis manuscript gathers five chapters. First, we give a short description of the LiDAR technology and an overview of the traditional 3D surface reconstruction from point cloud. Then we make a state-of-art of the shape-from –shading methods. LiDAR intensity is studied in a third chapter to define the strategy of distance effect correction and to set up the incidence angle vs intensity relationship. A fourth chapter gives the principal results of this thesis. It gathers the theoretical approach of the SFS algorithm developed in this thesis. We will provide its description and results when applied to synthetic images. Finally, a last chapter introduces results of leaves reconstruction
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 джерелаSu, Ning. "Cutting force modeling and optimization in 3D plane surface machining." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ39890.pdf.
Повний текст джерелаSingels, Wynand. "An application of photogrammetry in the petrochemical industry." Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/2296.
Повний текст джерелаWhen building or improving a petrochemical plant, drawings are used extensively in the design process. However, existing petrochemical plants seldom match their drawings, or the drawings are lost, forcing the need to generate a 3D model of the structure of the plant. In this thesis photogrammetry is investigated as a method of generating a digital 3D model of an existing plant. Camera modeling, target extraction and 3D reconstruction are discussed in detail, and a real-world system is investigated.
Al-Douri, Firas A. Salman. "Impact of utilizing 3D digital urban models on the design content of urban design plans in US cities." Texas A&M University, 2006. http://hdl.handle.net/1969.1/4324.
Повний текст джерелаCura, Rémi. "Inverse procedural Street Modelling : from interactive to automatic reconstruction." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1034/document.
Повний текст джерелаWorld urban population is growing fast, and so are cities, inducing an urgent need for city planning and management.Increasing amounts of data are required as cities are becoming larger, "Smarter", and as more related applications necessitate those data (planning, virtual tourism, traffic simulation, etc.).Data related to cities then become larger and are integrated into more complex city model.Roads and streets are an essential part of the city, being the interface between public and private space, and between urban usages.Modelling streets (or street reconstruction) is difficult because streets can be very different from each other (in layout, functions, morphology) and contain widely varying urban features (furniture, markings, traffic signs), at different scales.In this thesis, we propose an automatic and semi-automatic framework to model and reconstruct streets using the inverse procedural modelling paradigm.The main guiding principle is to generate a procedural generic model and then to adapt it to reality using observations.In our framework, a "best guess" road model is first generated from very little information (road axis network and associated attributes), that is available in most of national databases.This road model is then fitted to observations by combining in-base interactive user edition (using common GIS software as graphical interface) with semi-automated optimisation.The optimisation approach adapts the road model so it fits observations of urban features extracted from diverse sensing data.Both street generation (StreetGen) and interactions happen in a database server, as well as the management of large amount of street Lidar data (sensing data) as the observations using a Point Cloud Server.We test our methods on the entire Paris city, whose streets are generated in a few minutes, can be edited interactively (<0.3 s) by several concurrent users.Automatic fitting (few m) shows promising results (average distance to ground truth reduced from 2.0 m to 0.5m).In the future, this method could be mixed with others dedicated to reconstruction of buildings, vegetation, etc., so an affordable, precise, and up to date City model can be obtained quickly and semi-automatically.This will also allow to such models to be used in other application areas.Indeed, the possibility to have common, more generic, city models is an important challenge given the cost an complexity of their construction
Turunc, Cagri. "An Implementation Of 3d Slam With Planar Segments." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12614928/index.pdf.
Повний текст джерелаit is believed that, contribution of adding a direction vector to 3D features is investigated and illustrated via graphs of monte-carlo simulations. At the second part of the work, a scanner sensor system with IR distance finder is designed and constructed. An algorithm was presented to extract planar features from data collected by sensor system. A noise model was proposed for output features of sensor and 4D EKF SLAM algorithm was executed via extracted features of scanner system. By this way, performance of 4D EKF SLAM algorithm is tested with real sensor data and output results are compared with 3D features. So in this work, contribution of using 4D features instead of 3D ones was examined via comparing performance of 3D and 4D algorithms with simulation results and real sensor data.
Panchal, Dhaval. "Failure and damage progression of 3D woven composite structures subjected to out-of-plane loading." Thesis, Loughborough University, 2017. https://dspace.lboro.ac.uk/2134/33284.
Повний текст джерелаBui, 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 modeling"
Liu, Jia, Zhiguo Jiang, Hongjun Li, Weilong Ding, and Xiaopeng Zhang. "3D Plant Modeling Based on BP Neural Network." In Lecture Notes in Computer Science, 109–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-50544-1_10.
Повний текст джерелаNakini, Tushar Kanta Das, and Guilherme N. DeSouza. "Distortion Correction in 3D-Modeling of Root Systems for Plant Phenotyping." In Computer Vision - ECCV 2014 Workshops, 140–57. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16220-1_11.
Повний текст джерелаPaviot, Thomas, Virginie Fortineau, Samir Lamouri, and Ludovic Louis-Sidney. "A Modeling Language for 3D Process Plant Layout Representation, Exchange and Visualization." In Product Lifecycle Management. Towards Knowledge-Rich Enterprises, 478–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35758-9_43.
Повний текст джерелаSantos, Thiago Teixeira, Luciano Vieira Koenigkan, Jayme Garcia Arnal Barbedo, and Gustavo Costa Rodrigues. "3D Plant Modeling: Localization, Mapping and Segmentation for Plant Phenotyping Using a Single Hand-held Camera." In Computer Vision - ECCV 2014 Workshops, 247–63. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16220-1_18.
Повний текст джерелаMurcia, Harold, David Sanabria, Dehyro Méndez, and Manuel G. Forero. "A Comparative Study of 3D Plant Modeling Systems Based on Low-Cost 2D LiDAR and Kinect." In Lecture Notes in Computer Science, 272–81. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77004-4_26.
Повний текст джерелаLewis, P. "3D Canopy Modelling as a Tool in Remote-Sensing Research." In Functional-Structural Plant Modelling in Crop Production, 219–29. Dordrecht: Springer Netherlands, 2007. http://dx.doi.org/10.1007/1-4020-6034-3_19.
Повний текст джерелаLiu, Chuan, Jiaqi Shen, Yue Ren, and Hao Zheng. "Pipes of AI – Machine Learning Assisted 3D Modeling Design." In Proceedings of the 2020 DigitalFUTURES, 17–26. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4400-6_2.
Повний текст джерелаSwaileh, Wassim, Michel Jordan, and Dimitris Kotzinos. "3D Modelling Approach for Ancient Floor Plans’ Quick Browsing." In Document Analysis Systems, 629–43. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06555-2_42.
Повний текст джерелаBolognesi, Cecilia Maria, Eva-Lotta Kurkinen, and Per Andersson. "Digital Tools for Fast Mapping of Buildings." In Innovative Tools and Methods Using BIM for an Efficient Renovation in Buildings, 51–62. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04670-4_4.
Повний текст джерелаArmand, Patrick, and Christophe Duchenne. "3D Multi-scale Weather and Dispersion Models Applied to Assess the Impact of Industrial Plants on Human Health and the Environment." In Air Pollution Modeling and its Application XXVIII, 51–63. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12786-1_7.
Повний текст джерелаТези доповідей конференцій з теми "Plant 3D modeling"
Long, Jie, and Michael D. Jones. "3D tree modeling using motion capture." In 2012 IEEE 4th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA). IEEE, 2012. http://dx.doi.org/10.1109/pma.2012.6524841.
Повний текст джерелаGuo, Jianwei, Zhanglin Cheng, Shibiao Xu, and Xiaopeng Zhang. "Realistic procedural plant modeling guided by 3D point cloud." In SIGGRAPH '17: Special Interest Group on Computer Graphics and Interactive Techniques Conference. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3102163.3102193.
Повний текст джерелаGarcia, Manuel F., Diego Mendez, and Julian D. Colorado. "Fusion of Low-Density LiDAR Data with RGB Images for Plant 3D Modeling." In 2020 Virtual Symposium in Plant Omics Sciences (OMICAS). IEEE, 2020. http://dx.doi.org/10.1109/omicas52284.2020.9535650.
Повний текст джерелаWeilong Ding, Zhijun Cheng, and Yuping Zhang. "A new parametric method for modeling 3D structure of plant." In 2008 7th World Congress on Intelligent Control and Automation. IEEE, 2008. http://dx.doi.org/10.1109/wcica.2008.4593745.
Повний текст джерелаMurcia, Harold F., David A. Sanabria, Dehyro-Mendez, and Manuel G. Forero. "Development of a Simulation Tool for 3D Plant Modeling based on 2D LiDAR Sensor." In 2020 Virtual Symposium in Plant Omics Sciences (OMICAS). IEEE, 2020. http://dx.doi.org/10.1109/omicas52284.2020.9535651.
Повний текст джерелаJaeger, M., S. Sabatier, P. Borianne, P. de Reffye, Y. Gang, V. Letort, X. P. Zhang, and M. Z. Kang. "Data visualization for vegetal landscapes: Building 3D representations of organ biomass compartments: How plant production could constrain 3D lollypop-like representations." In 2018 6th International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA). IEEE, 2018. http://dx.doi.org/10.1109/pma.2018.8611608.
Повний текст джерелаWu, Zhongke, Mingquan Zhou, Xingce Wang, Xuefeng Ao, and Rongqing Song. "An Interactive System of Modeling 3D Trees with Ball B-Spline Curves." In 2006 International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA). IEEE, 2006. http://dx.doi.org/10.1109/pma.2006.38.
Повний текст джерелаLei, Hongyun, Chengda Lin, Ruifang Zhai, and Yidan Yao. "Research on rapeseed plant modeling and optimization from 3D point cloud." In 2015 Fourth International Conference on Agro-Geoinformatics (Agro-Geoinformatics). IEEE, 2015. http://dx.doi.org/10.1109/agro-geoinformatics.2015.7248128.
Повний текст джерелаDanjon, Fr, David H. Barker, Michael Drexhage, and Alexia Stokes. "Analysis of 3D Structural Root Architecture Data of Trees Grown on Slopes." In 2006 International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA). IEEE, 2006. http://dx.doi.org/10.1109/pma.2006.54.
Повний текст джерелаTang, Yige, Zhongke Wu, and Mingquan Zhou. "Sketching 3D Plant Based on Ball B-Spline Curves and L-system." In 2009 Third International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications (PMA). IEEE, 2009. http://dx.doi.org/10.1109/pma.2009.41.
Повний текст джерелаЗвіти організацій з теми "Plant 3D modeling"
Nathan V. Hoffer, Piyush Sabharwall, and Nolan A. Anderson. Modeling a Helical-coil Steam Generator in RELAP5-3D for the Next Generation Nuclear Plant. Office of Scientific and Technical Information (OSTI), January 2011. http://dx.doi.org/10.2172/1004263.
Повний текст джерелаTuller, Markus, Asher Bar-Tal, Hadar Heller, and Michal Amichai. Optimization of advanced greenhouse substrates based on physicochemical characterization, numerical simulations, and tomato growth experiments. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7600009.bard.
Повний текст джерелаHordiienko, Valentyna V., Galyna V. Marchuk, Tetiana A. Vakaliuk, and Andrey V. Pikilnyak. Development of a model of the solar system in AR and 3D. [б. в.], November 2020. http://dx.doi.org/10.31812/123456789/4410.
Повний текст джерелаJindal, Ashish, Christopher Moore, Andrew Fierro, and Matthew Hopkins. Full 3D Kinetic Modeling and Quantification of Positive Streamer Evolution in an Azimuthally Swept Pin-to-Plane Wedge Geometry. Office of Scientific and Technical Information (OSTI), September 2022. http://dx.doi.org/10.2172/1888448.
Повний текст джерелаModeling a Printed Circuit Heat Exchanger with RELAP5-3D for the Next Generation Nuclear Plant. Office of Scientific and Technical Information (OSTI), December 2010. http://dx.doi.org/10.2172/1004237.
Повний текст джерела