Literatura científica selecionada sobre o tema "3D body modelling"
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Artigos de revistas sobre o assunto "3D body modelling"
Arlt, Frank, e Amin Marach. "CAD modelling of a human 3D child body". International Journal of Industrial Ergonomics 22, n.º 4-5 (novembro de 1998): 333–41. http://dx.doi.org/10.1016/s0169-8141(97)00086-3.
Texto completo da fonteŠpelić, Ivana, e Slavenka Petrak. "Complexity of 3D human body scan data modelling". TEKSTILEC 61, n.º 4 (17 de dezembro de 2018): 235–44. http://dx.doi.org/10.14502/tekstilec2018.61.235-244.
Texto completo da fonteMilosevic, Paula, e Slavica Bogovic. "3D technologies in individualized chest protector modelling". Textile & Leather Review 1, n.º 2 (setembro de 2018): 46–55. http://dx.doi.org/10.31881/tlr.2018.vol1.iss2.p46-55.a6.
Texto completo da fonteGu, Bingfei, Md Kawysar Ahmed, Zejun Zhong e Juanfeng Jin. "3D female upper body modelling based on 2D images". International Journal of Clothing Science and Technology 32, n.º 4 (8 de janeiro de 2020): 471–82. http://dx.doi.org/10.1108/ijcst-03-2019-0042.
Texto completo da fonteTyson, Stephen, e Joost Herweijer. "Knowledge management and 3D modelling: overview and application to iterative 3D modelling workflows". APPEA Journal 51, n.º 2 (2011): 683. http://dx.doi.org/10.1071/aj10063.
Texto completo da fonteMarkiewicz, P. J., M. Tamal, P. J. Julyan, D. L. Hastings e A. J. Reader. "High accuracy multiple scatter modelling for 3D whole body PET". Physics in Medicine and Biology 52, n.º 3 (16 de janeiro de 2007): 829–47. http://dx.doi.org/10.1088/0031-9155/52/3/021.
Texto completo da fonteThelwell, Michael, Alice Bullas, Andreas Kühnapfel, John Hart, Peter Ahnert, Jon Wheat, Markus Loeffler, Markus Scholz e Simon Choppin. "Modelling of human torso shape variation inferred by geometric morphometrics". PLOS ONE 17, n.º 3 (10 de março de 2022): e0265255. http://dx.doi.org/10.1371/journal.pone.0265255.
Texto completo da fonteRudolf, A., Z. Stjepanović e A. Cupar. "DESIGN OF GARMENTS USING ADAPTABLE DIGITAL BODY MODELS". TEXTEH Proceedings 2021 (22 de outubro de 2021): 9–17. http://dx.doi.org/10.35530/tt.2021.09.
Texto completo da fonteGou, J., W. Zhou e L. Wu. "IMPLICIT THREE-DIMENSIONAL GEO-MODELLING BASED ON HRBF SURFACE". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W2 (5 de outubro de 2016): 63–66. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w2-63-2016.
Texto completo da fonteKudzia, Pawel, Erika Jackson e Genevieve Dumas. "Estimating body segment parameters from three-dimensional human body scans". PLOS ONE 17, n.º 1 (5 de janeiro de 2022): e0262296. http://dx.doi.org/10.1371/journal.pone.0262296.
Texto completo da fonteTeses / dissertações sobre o assunto "3D body modelling"
Dekker, Laura Daye. "3D human body modelling from range data". Thesis, University College London (University of London), 2000. http://discovery.ucl.ac.uk/1363354/.
Texto completo da fonteYassin, Nihad Jaro. "Application of parametric and solid modelling techniques to human body simulations". Thesis, Heriot-Watt University, 1992. http://hdl.handle.net/10399/1384.
Texto completo da fonteVyas, Keyur. "Modelling of 3D anisotropic turbulent flow in compound channels". Thesis, Loughborough University, 2007. https://dspace.lboro.ac.uk/2134/7976.
Texto completo da fonteElanattil, Shafeeq. "Non-rigid 3D reconstruction of the human body in motion". Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/205095/1/Shafeeq_Elanattil_Thesis.pdf.
Texto completo da fonteChi, Cheng. "Personalized pattern recommendation system of men’s shirts based on precise body measurement". Electronic Thesis or Diss., Centrale Lille Institut, 2022. http://www.theses.fr/2022CLIL0003.
Texto completo da fonteCommercial garment recommendation systems have been widely used in the apparel industry. However, existing research on digital garment design has focused on the technical development of the virtual design process, with little knowledge of traditional designers. The fit of a garment plays a significant role in whether a customer purchases that garment. In order to develop a well-fitting garment, designers and pattern makers should adjust the garment pattern several times until the customer is satisfied. Currently, there are three main disadvantages of traditional pattern-making: 1) it is very time-consuming and inefficient, 2) it relies too much on experienced designers, 3) the relationship between the human body shape and the garment is not fully explored. In practice, the designer plays a key role in a successful design process. There is a need to integrate the designer's knowledge and experience into current garment CAD systems to provide a feasible human-centered, low-cost design solution quickly for each personalized requirement. Also, data-based services such as recommendation systems, body shape classification, 3D body modelling, and garment fit assessment should be integrated into the apparel CAD system to improve the efficiency of the design process.Based on the above issues, in this thesis, a fit-oriented garment pattern intelligent recommendation system is proposed for supporting the design of personalized garment products. The system works in combination with a newly developed design process, i.e. body shape identification - design solution recommendation - 3D virtual presentation and evaluation - design parameter adjustment. This process can be repeated until the user is satisfied. The proposed recommendation system has been validated by some successful practical design cases
Rius, Ferrer Ignasi. "Motion Priors for Efficient Bayesian Tracking In Iluman Sequence Evaluation". Doctoral thesis, Universitat Autònoma de Barcelona, 2010. http://hdl.handle.net/10803/5798.
Texto completo da fonteEl treball presentat en aquesta Tesis esta enfocat a recuperar els parametres de moviment 3D d'un model del cos huma a partir de mesures incompletes i sorolloses d'una seqüencia d'imatges monocular. Aquestes mesures consisteixen en les posicions 2D d'un conjunt redult d'articulacions en el pla d'imatge. Amb aquesta fnalitat, proposem un nou model de moviment huma específc per cada acció, que és entrenat a partir de bases de dades de captures de moviment que contenen varies execucions d'una acció en particular, i que és utilitzat com a coneixement a priori en un esquema de fltratge de partícules.
Les postures del cos es representen emprant un model articulat simple i compacte que fa ús dels cosinus directors per tal de representar la direcció de les parts del cos en l'espai Cartesia 3D. Llavors, donada una acció, s'aplica l'Analisis de Components Principals (PCA) sobre les dades d'entrenament per tal d'aplicar reducció de dimensionalitat sobre les dades d'entrada altament correlacionades. Previament al pas d'entrenament del model d'acció, les seqüencies de moviment d'entrada són sincronitzades mitjançant un nou algoritme d'adaptació dens basat en Programació Dinamica. L'algoritme sincronitza totes les seqüencies de moviment d'una mateixa classe d'acció i és capa¡ de trobar una solució óptima en temps real.
Aleshores, s'apren un model d'acció probabilístic a partir dels exemples de movi¬ment sincronitzats que captura la variabilitat i l'evolució temporal del moviment del cos sencer durant una acció concreta. En particular, per cada acció, els parametres apresos són: una varietat representativa de l'acció que consisteix en l'execució mitjana de la mateixa, la desviació estandard de l'execució mitjana, els vectors de direcció mitjans de cada subseqüencia de moviment d'una llargada donada i l'error esperat en un instant de temps donat.
A continuació, s'utilitza el model específc per cada acció com a coneixement a priori sobre moviment huma que millora l'efciencia i robustesa de tot l'enfoc de seguiment basat en fltratge de partícules. En primer lloc, el model dinamic guia les partícules segons situacions similars apreses previament. A continuació, es restringeix l'espai d'estats per tal que tan sols les postures humanes més factibles siguin acceptades com a solucions valides a cada instant de temps. En conseqüencia, l'espai d'estats és explorat de manera més efcient ja que el conjunt de partícules cobreix les postures del cos més probables.
Finalment, es duen a terme experiments emprant seqüencies de test de varies bases de dades. Els resultats assenyalen que el nostre esquema de seguiment és capa d'estimar la confguració 3D aproximada d'un model de cos sencer, a partir tan sols de les posicions 2D d'un conjunt redult d'articulacions. També s'inclouen proves separades sobre el metode de sincronització de seqüencies i de la tecnica de comparació probabilística de les subseqüencies de moviment.
Recovering human motion by visual analysis is a challenging computer vision research area with a lot of potential applications. Model based tracking approaches, and in particular particle flters, formulate the problem as a Bayesian inference task whose aim is to sequentially estimate the distribution of the parameters of a human body model over time. These approaches strongly rely on good dynamical and observation models to predict and update confgurations of the human body according to mea surements from the image data. However, it is very difcult to design observation models which extract useful and reliable information from image sequences robustly. This results specially challenging in monocular tracking given that only one viewpoint from the scene is available. Therefore, to overcome these limitations strong motion priors are needed to guide the exploration of the state space.
The work presented in this Thesis is aimed to retrieve the 3D motion parameters of a human body model from incomplete and noisy measurements of a monocular image sequence. These measurements consist of the 2D positions of a reduced set of joints in the image plane. Towards this end, we present a novel action specifc model of human motion which is trained from several databases of real motion captured performances of an action, and is used as a priori knowledge within a particle fltering scheme.
Body postures are represented by means of a simple and compact stick fgure model which uses direction cosines to represent the direction of body limbs in the 3D Cartesian space. Then, for a given action, Principal Component Analysis is applied to the training data to perform dimensionality reduction over the highly correlated input data. Before the learning stage of the action model, the input motion performances are synchronized by means of a novel dense matching algorithm based on Dynamic Programming. The algorithm synchronizes all the motion sequences of the same action class, fnding an optimal solution in real time.
Then, a probabilistic action model is learnt, based on the synchronized motion examples, which captures the variability and temporal evolution of full body motion within a specifc action. In particular, for each action, the parameters learnt are: a representative manifold for the action consisting of its mean performance, the stan dard deviation from the mean performance, the mean observed direction vectors from each motion subsequence of a given length and the expected error at a given time instant.
Subsequently, the action specifc model is used as a priori knowledge on human motion which improves the efciency and robustness of the overall particle fltering tracking framework. First, the dynamic model guides the particles according to similar situations previously learnt. Then, the state space is constrained so only feasible human postures are accepted as valid solutions at each time step. As a result, the state space is explored more efciently as the particle set covers the most probable body postures.
Finally, experiments are carried out using test sequences from several motion databases. Results point out that our tracker scheme is able to estimate the rough 3D confguration of a full body model providing only the 2D positions of a reduced set of joints. Separate tests on the sequence synchronization method and the subsequence probabilistic matching technique are also provided.
Keywords: Human Motion Modeling; Particle fltering; Monocular Full Body 3D Tracking.
Topics: Image Processing; Computer Vision; Scene Understanding; Machine Intelligence; Machine Vision Applications; Video-Sequence Evaluation
Tecklenburg, Gerhard. "Design of body assemblies with distributed tasks under the support of parametric associative design (PAD)". Thesis, University of Hertfordshire, 2011. http://hdl.handle.net/2299/5809.
Texto completo da fonteCapítulos de livros sobre o assunto "3D body modelling"
Alemany, S., A. Ballester, E. Parrilla, A. Pierola, J. Uriel, B. Nacher, A. Remon et al. "3D Body Modelling and Applications". In Advances in Intelligent Systems and Computing, 623–36. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96065-4_66.
Texto completo da fonteKuchmin, A. Yu, e Somar Karheily. "Automatic 3D Human Body Modelling". In Smart Electromechanical Systems: The Central Nervous System, 83–94. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53327-8_7.
Texto completo da fonteGu, Jin, Terry Chang, Ivan Mak, S. Gopalsamy, H. C. Shen e M. M. F. Yuen. "A 3D Reconstruction System for Human Body Modeling". In Modelling and Motion Capture Techniques for Virtual Environments, 229–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-49384-0_18.
Texto completo da fonteBardaro, Gianluca, Luca Bascetta, Francesco Casella e Matteo Matteucci. "Advancement in Multi-body Physics Modeling for 3D Graphical Robot Simulators". In Modelling and Simulation for Autonomous Systems, 189–95. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47605-6_15.
Texto completo da fonteAwrejcewicz, Jan, e Grzegorz Kudra. "Modelling of Frictional Contacts in 3D Dynamics of a Rigid Body". In Springer Proceedings in Physics, 3–12. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54136-1_1.
Texto completo da fontePeeters, Thomas, Jochen Vleugels, Stijn Verwulgen, Femke Danckaers, Toon Huysmans, Jan Sijbers e Guido De Bruyne. "A Comparative Study Between Three Measurement Methods to Predict 3D Body Dimensions Using Shape Modelling". In Advances in Intelligent Systems and Computing, 464–70. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20216-3_43.
Texto completo da fonteNikolova, Gergana, Daniel Dantchev, Vladimir Kotev e Mihail Tsveov. "The Human Body and Weightlessness: Mass-Inertial Characteristics in One of the Basic Positions Selected by NASA via 3D Mathematical Modelling". In 8th European Medical and Biological Engineering Conference, 1092–100. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64610-3_123.
Texto completo da fonteAmbu, Rita, e Michele Calì. "Assessment of High Porosity Lattice Structures for Lightweight Applications". In Lecture Notes in Mechanical Engineering, 15–26. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18326-3_2.
Texto completo da fonteAbadía, Mercedes Farjas, Manuel Sillero Quintana e Pedro Ángel Merino Calvo. "Application of Topographical Capture Techniques for Modelling Virtual Reality". In Geographic Information Systems, 970–90. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2038-4.ch060.
Texto completo da fonteAbadía, Mercedes Farjas, Manuel Sillero Quintana e Pedro Ángel Merino Calvo. "Application of Topographical Capture Techniques for Modelling Virtual Reality". In Virtual Technologies for Business and Industrial Applications, 181–200. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-61520-631-5.ch011.
Texto completo da fonteTrabalhos de conferências sobre o assunto "3D body modelling"
"ON-LINE 3D BODY MODELLING FOR AUGMENTED REALITY". In International Conference on Computer Graphics Theory and Applications. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003866304720479.
Texto completo da fonteLu, Guo-Dong, e Wei-Yan Deng. "Human Body Feature Curve Generating Method Based on Neural Network for 3D Human Body Modelling". In 2008 Congress on Image and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/cisp.2008.343.
Texto completo da fonteSTANKOVIC, Kristina, Femke DANCKAERS, Brian G. BOOTH, Fien BURG, Saartje DUERINCK, Jan SIJBERS e Toon HUYSMANS. "Foot Abnormality Mapping using Statistical Shape Modelling". In 7th International Conference on 3D Body Scanning Technologies, Lugano, Switzerland, 30 Nov.-1 Dec. 2016. Ascona, Switzerland: Hometrica Consulting - Dr. Nicola D'Apuzzo, 2016. http://dx.doi.org/10.15221/16.070.
Texto completo da fontePsikuta, Agnes, Joanna Frackiewicz-Kaczmarek e Rene M. Rossi. "Use of 3D Body Scanning Technique for Heat and Mass Transfer Modelling in Clothing". In 3rd International Conference on 3D Body Scanning Technologies, Lugano, Switzerland, 16-17 October 2012. Ascona, Switzerland: Hometrica Consulting - Dr. Nicola D'Apuzzo, 2012. http://dx.doi.org/10.15221/12.051.
Texto completo da fonteBardaro, Gianluca, Luca Bascetta, Francesco Casella e Matteo Matteucci. "Using Modelica for advanced Multi-Body modelling in 3D graphical robotic simulators". In The 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017. Linköping University Electronic Press, 2017. http://dx.doi.org/10.3384/ecp17132887.
Texto completo da fonteXU, Tingyu, Huanyun WEI, Yue XIN e Longlin ZHANG. "Conversion Technology of Clothing Patterns from 3D Modelling to 2D Templates Based on Individual Point-Cloud". In 6th International Conference on 3D Body Scanning Technologies, Lugano, Switzerland, 27-28 October 2015. Ascona, Switzerland: Hometrica Consulting - Dr. Nicola D'Apuzzo, 2015. http://dx.doi.org/10.15221/15.134.
Texto completo da fonteHovaneca, Michal, Teodor Tóthb, Viktória Rajťúkováb, Hana Pačaiováa e Jozef Živčákb. "Application of 3D Full Body Scanners in Ergonomics". In Applied Human Factors and Ergonomics Conference. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe100814.
Texto completo da fonteSpitzer, K., e H.-J. Kümpel. "A New FD Method for 3D Resistivity Modelling with Application to a Phonolithic Body". In 57th EAEG Meeting. Netherlands: EAGE Publications BV, 1995. http://dx.doi.org/10.3997/2214-4609.201409365.
Texto completo da fonte"SEGMENTATION AND MODELLING OF FULL HUMAN BODY SHAPE FROM 3D SCAN DATA: A SURVEY". In International Conference on Computer Vision Theory and Applications. SciTePress - Science and and Technology Publications, 2006. http://dx.doi.org/10.5220/0001367401890197.
Texto completo da fonteBARBERO-GARCIA, Ines, Jose Luis LERMA e Pablo MIRANDA. "Automatic Low-Cost Tool for Head 3D Modelling and Cranial Deformation Analysis in Infants". In 3DBODY.TECH 2019 - 10th International Conference and Exhibition on 3D Body Scanning and Processing Technologies, Lugano, Switzerland, 22-23 Oct. 2019. Ascona, Switzerland: Hometrica Consulting - Dr. Nicola D'Apuzzo, 2019. http://dx.doi.org/10.15221/19.009.
Texto completo da fonte