Tesi sul tema "Analysis Motion"
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Oztekin, Kaan. "Textured Motion Analysis". Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606795/index.pdf.
Jin, Ning. "Human motion analysis". Thesis, University of Surrey, 2007. http://epubs.surrey.ac.uk/804406/.
MISHRA, OM. "HUMAN MOTION ANALYSIS". Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2020. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18772.
Wong, Wai-ning Kris. "Lumbar spinal motion analysis". Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36611773.
Wong, Wai-ning Kris, e 黃偉寧. "Lumbar spinal motion analysis". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36611773.
MORO, MATTEO. "Markerless Human Motion Analysis". Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1080400.
Xiao, Zhidong. "Motion capture based motion analysis and motion synthesis for human-like character animation". Thesis, Bournemouth University, 2009. http://eprints.bournemouth.ac.uk/14590/.
Cheng, Xin. "Feature-based motion estimation and motion segmentation". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0016/MQ55493.pdf.
Aksu, tIbrahim. "Performance analysis of image motion analysis algorithms". Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/28443.
Pedersen, Emil Aasland. "Motion analysis of Semi-Submersible". Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for marin teknikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-19419.
Gardner, Warren F. "Constraints for robust motion analysis". Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/9176.
Tresadern, Phil. "Visual analysis of articulated motion". Thesis, University of Oxford, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436970.
Chan, Chee Seng. "Fuzzy qualitative human motion analysis". Thesis, University of Portsmouth, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.494009.
Dobie, Mark Ralph. "Motion analysis in multimedia systems". Thesis, University of Southampton, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359240.
Edmison, Joshua Nathaniel. "Electronic Textiles for Motion Analysis". Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/9978.
Master of Science
Teixeira, Euler da Cunha Francisco. "Motion analysis of clarinet performers". Universidade Federal de Minas Gerais, 2014. http://hdl.handle.net/1843/BUOS-9UJRW7.
A expressividade musical é um conceito difícil de ser formalizado com base em dados objetivos e sua análise geralmente depende de algum tipo de avaliação subjetiva. Atualmente há uma crescente busca por métodos e descritores capazes de extrair, quantificar, analisar e sintetizar essas intenções expressivas. Isso vem sendo feito principalmente através da análise de áudio das execuções musicais, identificando os parâmetros acústicos capazes de descrever o seu conteúdo expressivo. Esse estudo expande os métodos de análise acústica para a investigação das intenções expressivas dos músicos, incorporando informações sobre seus movimentos corporais durante as execuções musicais. Uma metodologia é proposta para a definição e a análise dos gestos físicos realizados por eles ao tocarem, e para a extração de parâmetros de movimento que possam ser relacionados objetivamente às suas intenções expressivas e à estrutura musical. A consistência gestual de 13 clarinetistas é avaliada durante diversas execuções musicais, estabelecendo uma relação objetiva entre seus padrões gestuais expressivos e a estrutura musical de dois excertos de Mozart e Brahms. Um método é definido para representar, segmentar e analisar os padrões de recorrência nos dados de movimento das execuções. Gestos físicos recorrentes foram extraídos durante execuções de clarineta e analisados com base em parâmetros gestuais, comparando diferentes músicos, passagens musicais e condições experimentais. Os resultados indicam sequências recorrentes de gestos de clarineta em regiões dos excertos relacionadas a momentos de alta relevância musical. Uma análise correspondente é conduzida sobre os dados acústicos, buscando padrões paramétricos relacionados, capazes de validar os resultados da análise de movimento. As informações obtidas podem ser usadas para definir um método integrado de parametrização e quantificação das intenções expressivas dos músicos. Esse método pode ser incorporado a sistemas de síntese, reconhecimento, ensino e análise de música, ou utilizado em estudos teóricos nas áreas de musicologia, cognição e fisiologia humanas, possibilitando a definição de um significado musical para os gestos físicos de músicos durante execuções musicais.
López, Méndez Adolfo. "Articulated models for human motion analysis". Doctoral thesis, Universitat Politècnica de Catalunya, 2012. http://hdl.handle.net/10803/112124.
L’anàlisi del moviment humà es una area de visió per computador que, en les últimes dècades, ha atret l'interès de la comunitat científica. L’anàlisi de moviment inclou temes com el seguiment del cos humà, el reconeixement d'accions i patrons de comportament, o la segmentació del moviment humà. Tots aquests camps suposen un repte a causa de diferents raons, però especialment a la perspectiva de captura de les escenes a analitzar i també a l’absència d'una semàntica precisa associada a les accions i el moviment humà. La comunitat de visió per computador ha abordat l’anàlisi del moviment humà des de diverses perspectives. Els primers enfocaments es basen en models articulats del cos humà. Aquests models representen el cos com una estructura esqueletal tridimensional. No obstant, a causa de la dificultat i el cost computacional de l’estimació d'aquesta estructura articulada a partir de vídeo, la investigació s'ha anat enfocant, en els últims anys, cap a l’anàlisi de moviment humà basat en característiques de baix nivell. Malgrat obtenir resultats impressionants en diverses tasques, les característiques de baix nivell estan normalment condicionades per l’aparença i punt de vista, cosa que fa difícil la seva aplicació en diferents escenaris. Avui dia, l'augment de la potència de càlcul, la disponibilitat massiva de dades i la irrupció de les càmares de profunditat de baix cost han proporcionat un escenari que permet reconsiderar l’anàlisi de moviment humà a través de models articulats. L'anàlisi i comprensió del moviment humà a través de la informació tridimensional segueix sent un enfocament crucial per obtenir millors models dinàmics al voltant del moviment del cos humà. Per això, els models articulats del cos humà, que ofereixen una representació compacta i invariant al punt de vista de la captura, són una eina per potenciar l'anàlisi de moviment. En aquesta tesi, es presenten diversos enfocaments per a l'anàlisi de moviment. En particular, s'aborda el problema de l'estimació de pose, el reconeixement d'accions i el clustering temporal del moviment humà. Els models articulats són el leitmotiv en tots els plantejaments presentats. En primer lloc, plantegem l’estimació de pose mitjançant la formulació d'un mètode jeràrquic d'anàlisi per síntesi en que els models s'utilitzen per generar hipòtesis que es contrasten amb vídeo. Fent servir la mateixa representació articulada del cos humà, es proposa una formulació del moviment humà per al reconeixement d'accions. La nostra hipòtesi és que les accions formen un conjunt de sistemes dinàmics subjacents que generen observacions en forma de sèries temporals. Aquestes sèries temporals són observades a través del model articulat. Aquesta hipòtesi s'utilitza amb la finalitat de desenvolupar mètodes de reconeixement basats en time-delay embeddings, una eina d’anàlisi de sèries temporals que no fa suposicions sobre la forma del sistema dinàmic subjacent. Finalment, es proposa un mètode per segmentar seqüències de moviment del cos humà en diferents comportaments o accions, sense necessitar un coneixement a priori del nombre d'accions en la seqüència. El nostre enfocament utilitza els models articulats del cos humà per aprendre una distància mètrica. Aquesta mètrica té com a objectiu capturar la semàntica implícita de les anotacions que es puguin trobar en altres bases de dades que continguin seqüències de moviment. Amb la finalitat de mesurar objectivament les nostres contribucions, els mètodes proposats són avaluats utilitzant bases de dades publiques.
Holmberg, Björn. "Towards markerless analysis of human motion /". Uppsala : Department of Information Technology, Uppsala University, 2005. http://www.it.uu.se/research/publications/lic/2005-011/.
Pochobradsky, Pavel. "Computerized system for time-motion analysis". Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=26306.
Giaccone, Paul. "Motion analysis of cinematographic image sequences". Thesis, Kingston University, 2000. http://eprints.kingston.ac.uk/20647/.
Saunders, Thomas. "Image motion analysis using inertial sensors". Thesis, University of Bath, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687346.
Holmberg, Björn. "Towards markerless analysis of human motion". Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-86359.
Neverova, Natalia. "Deep learning for human motion analysis". Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEI029/document.
The research goal of this work is to develop learning methods advancing automatic analysis and interpreting of human motion from different perspectives and based on various sources of information, such as images, video, depth, mocap data, audio and inertial sensors. For this purpose, we propose a several deep neural models and associated training algorithms for supervised classification and semi-supervised feature learning, as well as modelling of temporal dependencies, and show their efficiency on a set of fundamental tasks, including detection, classification, parameter estimation and user verification. First, we present a method for human action and gesture spotting and classification based on multi-scale and multi-modal deep learning from visual signals (such as video, depth and mocap data). Key to our technique is a training strategy which exploits, first, careful initialization of individual modalities and, second, gradual fusion involving random dropping of separate channels (dubbed ModDrop) for learning cross-modality correlations while preserving uniqueness of each modality-specific representation. Moving forward, from 1 to N mapping to continuous evaluation of gesture parameters, we address the problem of hand pose estimation and present a new method for regression on depth images, based on semi-supervised learning using convolutional deep neural networks, where raw depth data is fused with an intermediate representation in the form of a segmentation of the hand into parts. In separate but related work, we explore convolutional temporal models for human authentication based on their motion patterns. In this project, the data is captured by inertial sensors (such as accelerometers and gyroscopes) built in mobile devices. We propose an optimized shift-invariant dense convolutional mechanism and incorporate the discriminatively-trained dynamic features in a probabilistic generative framework taking into account temporal characteristics. Our results demonstrate, that human kinematics convey important information about user identity and can serve as a valuable component of multi-modal authentication systems
Parameswaran, Vasudev. "View-invariance in visual human motion analysis". College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/1408.
Thesis research directed by: Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Stenbro, Roger Eivind. "Performance Analysis of Nonlinearly Controlled Motion Systems". Thesis, Norwegian University of Science and Technology, Department of Engineering Cybernetics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9818.
In this thesis, we investige the applicability of the certain numerical methods for the solution of certain systems of partial differential equations. Numerical methods for this purpose are studied, in particular the finite element method. These systems arise from the study of extending performance analysis to general convergent nonlinear systems. It is argued that, for simplex meshes, the finite element method is not applicable to the systems. Further, it is argued that the finite element method should not be pursued as an alternative to the solution of these systems, as far better alternatives have recently been developed.
Erdem, Sezen. "Human Motion Analysis Via Axis Based Representations". Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608815/index.pdf.
Aristidou, Andreas. "Tracking and modelling motion for biomechanical analysis". Thesis, University of Cambridge, 2010. https://www.repository.cam.ac.uk/handle/1810/237554.
Rexhepi, Astrit. "Motion analysis using probabilistic and statistical reasoning". Thesis, University of Surrey, 2007. http://epubs.surrey.ac.uk/843205/.
Mitikiri, Praveen Kumar. "Rate distortion analysis for conditional motion estimation". Thesis, Wichita State University, 2008. http://hdl.handle.net/10057/2010.
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical and Computer Engineering
Includes bibliographic references (leaves 28-31)
Sharma, Yachna. "Surgical skill assessment using motion texture analysis". Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51890.
Rusaw, Shawn. "Sensor-based motion planning via nonsmooth analysis". Thesis, University of Oxford, 2002. http://ora.ox.ac.uk/objects/uuid:46fa490d-c4ca-45ad-9cd5-b1f11920863d.
Sokolov, Michael Adam. "Visual motion : algorithms for analysis and application". Thesis, Massachusetts Institute of Technology, 1990. http://hdl.handle.net/1721.1/70173.
Simoncelli, Eero Peter. "Distributed representation and analysis of visual motion". Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/12590.
Includes bibliographical references (leaves 171-179).
by Eero Peter Simoncelli.
Ph.D.
Kates, Mitchell (Mitchell H. ). "Player motion analysis : automatically classifying NBA plays". Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/100664.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 55-56).
Basketball is a team game, and an important task for coaches is analyzing the effectiveness of various offensive plays. Currently, teams spend a great deal of time examining video of past games. If teams could automatically classify plays, they could more effectively analyze their own plays and scout their opponents. In this thesis, we develop a methodology to help automatically classify a set of NBA plays using data from the SportVU optical tracking system, which tracks the position of each player and the ball 25 times per second. The problem is made challenging by the variations in how a play is run, the high proportion of possessions where no set play is run, the variance in length of plays, and the difficulty of acquiring a large number of labeled plays. We develop a framework for classifying plays using supervised machine learning. In our approach, we incorporate a novel sliding block algorithm that improves our classifier by accounting for the difference in play lengths. We also use a variant of the traditional one vs. all multi-class SVM. This approach is well suited to distinguish labeled plays from free motion and unlabeled plays. This thesis demonstrates that we can use SportVU data to automatically differentiate plays. We selected a total of six plays to classify, where each play had at least 20 labeled instances. We also added a large selection of plays that were not one of these six and labeled them as Other. Our framework correctly predicted the play with an accuracy of 72.6% and an F-score of .727. We also propose a framework, based on our engineered features, to extend our research to unlabeled plays.
by Mitchell Kates.
M. Eng.
Abedan, Kondori Farid. "Human Motion Analysis for Creating Immersive Experiences". Licentiate thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-55832.
Yang, Cheng. "Multimedia motion analysis for remote health monitoring". Thesis, University of Strathclyde, 2017. http://digitool.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=27952.
Hosseini, Babak [Verfasser]. "Interpretable analysis of motion data / Babak Hosseini". Bielefeld : Universitätsbibliothek Bielefeld, 2021. http://d-nb.info/1237815509/34.
Mitikiri, Praveen Kumar Namuduri Kamiswara. "Rate distortion analysis for conditional motion estimation". A link to full text of this thesis in SOAR, 2008. http://hdl.handle.net/10057/2010.
Copyright 2008 by Praveen Kumar Mitikiri. All Rights Reserved. Includes bibliographical references (leaves 28-31).
Conrad, Bryan Preston. "Three-dimensional kinematic analysis of spine motion". [Gainesville, Fla.] : University of Florida, 2009. http://purl.fcla.edu/fcla/etd/UFE0041210.
Jiang, Hai. "Quantitative deformable motion estimation for biophysical analysis /". free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p3144427.
Ming, Kee-ying Thomas. "An analysis of the filmic : a philosophical grounding for film aesthetics /". [Hong Kong] : University of Hong Kong, 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B15949941.
Ye, Ming. "Robust visual motion analysis : piecewise-smooth optical flow and motion-based detection and tracking /". Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/6077.
Apthorp, Deborah Miriam. "The role of motion streaks in human visual motion perception". Thesis, The University of Sydney, 2011. http://hdl.handle.net/2123/7432.
Braude, David Adam. "Head motion synthesis : evaluation and a template motion approach". Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/20418.
Kruger, Stefan A. "Motion analysis and estimation using multiresolution affine models". Thesis, University of Bristol, 1998. http://hdl.handle.net/1983/f1c3201e-cc47-4064-a897-5264498767bf.
IKBAL, MOHAMED SADIQ. "Motion Generation and Planning System for a Virtual Reality Motion Simulator: Development, Integration, and Analysis". Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1046138.
Robinson, M. Dirk. "Estimation theoretic analysis of motion in image sequences /". Diss., Digital Dissertations Database. Restricted to UC campuses, 2004. http://uclibs.org/PID/11984.
Dane, Gökc̦e. "Temporal frame interpolation by motion analysis and processing /". Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2005. http://wwwlib.umi.com/cr/ucsd/fullcit?p3191984.
Coll, Pedro F. "Target motion analysis from a diesel submarine's perspective". Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1994. http://handle.dtic.mil/100.2/ADA289557.
Sarigol, Ebru. "Numerical And Experimental Analysis Of Flapping Wing Motion". Phd thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608613/index.pdf.