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Dissertations / Theses on the topic 'Gesture Recognition'

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Published: 4 June 2021

Last updated: 25 July 2025

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1

Davis, James W. "Gesture recognition." Honors in the Major Thesis, University of Central Florida, 1994. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/126.

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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf.edu/Systems/DigitalInitiatives/DigitalCollections/InternetDistributionConsentAgreementForm.pdf You may also contact the project coordinator, Kerri Bottorff, at kerri.bottorff@ucf.edu for more information.<br>Bachelors<br>Arts and Sciences<br>Computer Science

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2

Cheng, You-Chi. "Robust gesture recognition." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53492.

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It is a challenging problem to make a general hand gesture recognition system work in a practical operation environment. In this study, it is mainly focused on recognizing English letters and digits performed near the steering wheel of a car and captured by a video camera. Like most human computer interaction (HCI) scenarios, the in-car gesture recognition suffers from various robustness issues, including multiple human factors and highly varying lighting conditions. It therefore brings up quite a few research issues to be addressed. First, multiple gesturing alternatives may share the same me

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3

Kaâniche, Mohamed Bécha. "Human gesture recognition." Nice, 2009. http://www.theses.fr/2009NICE4032.

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Dans cette thèse, nous voulons reconnaître les gestes (par ex. Lever la main) et plus généralement les actions brèves (par ex. Tomber, se baisser) effectués par un individu. De nombreux travaux ont été proposés afin de reconnaître des gestes dans un contexte précis (par ex. En laboratoire) à l’aide d’une multiplicité de capteurs (par ex. Réseaux de cameras ou individu observé muni de marqueurs). Malgré ces hypothèses simplificatrices, la reconnaissance de gestes reste souvent ambiguë en fonction de la position de l’individu par rapport aux caméras. Nous proposons de réduire ces hypothèses afin

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Semprini, Mattia. "Gesture Recognition: una panoramica." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15672/.

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Per decenni, l’uomo ha interagito con i calcolatori e altri dispositivi quasi esclusivamente premendo i tasti e facendo "click" sul mouse. Al giorno d’oggi, vi è un grande cambiamento in atto a seguito di una ondata di nuove tecnologie che rispondono alle azioni più naturali, come il movimento delle mani o dell’intero corpo. Il mercato tecnologico è stato scosso in un primo momento dalla sostituzione delle tecniche di interazione standard con approcci di tipo "touch and motion sensing"; il passo successivo è l’introduzione di tecniche e tecnologie che permettano all’utente di accedere e manipo

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Gingir, Emrah. "Hand Gesture Recognition System." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612532/index.pdf.

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This thesis study presents a hand gesture recognition system, which replaces input devices like keyboard and mouse with static and dynamic hand gestures, for interactive computer applications. Despite the increase in the attention of such systems there are still certain limitations in literature. Most applications require different constraints like having distinct lightning conditions, usage of a specific camera, making the user wear a multi-colored glove or need lots of training data. The system mentioned in this study disables all these restrictions and provides an adaptive, effort free envi

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6

Dang, Darren Phi Bang. "Template based gesture recognition." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/41404.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.<br>Includes bibliographical references (p. 65-66).<br>by Darren PHi Bang Dang.<br>M.S.

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7

Wang, Lei. "Personalized Dynamic Hand Gesture Recognition." Thesis, KTH, Medieteknik och interaktionsdesign, MID, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231345.

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Human gestures, with the spatial-temporal variability, are difficult to be recognized by a generic model or classifier that are applicable for everyone. To address the problem, in this thesis, personalized dynamic gesture recognition approaches are proposed. Specifically, based on Dynamic Time Warping(DTW), a novel concept of Subject Relation Network is introduced to describe the similarity of subjects in performing dynamic gestures, which offers a brand new view for gesture recognition. By clustering or arranging training subjects based on the network, two personalization algorithms are propo

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8

Espinoza, Victor. "Gesture Recognition in Tennis Biomechanics." Master's thesis, Temple University Libraries, 2018. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/530096.

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Electrical and Computer Engineering<br>M.S.E.E.<br>The purpose of this study is to create a gesture recognition system that interprets motion capture data of a tennis player to determine which biomechanical aspects of a tennis swing best correlate to a swing efficacy. For our learning set this work aimed to record 50 tennis athletes of similar competency with the Microsoft Kinect performing standard tennis swings in the presence of different targets. With the acquired data we extracted biomechanical features that hypothetically correlated to ball trajectory using proper technique and tested th

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Nygård, Espen Solberg. "Multi-touch Interaction with Gesture Recognition." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9126.

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<p>This master's thesis explores the world of multi-touch interaction with gesture recognition. The focus is on camera based multi-touch techniques, as these provide a new dimension to multi-touch with its ability to recognize objects. During the project, a multi-touch table based on the technology Diffused Surface Illumination has been built. In addition to building a table, a complete gesture recognition system has been implemented, and different gesture recognition algorithms have been successfully tested in a multi-touch environment. The goal with this table, and the accompanying gesture r

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10

Khan, Muhammad. "Hand Gesture Detection & Recognition System." Thesis, Högskolan Dalarna, Datateknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:du-6496.

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The project introduces an application using computer vision for Hand gesture recognition. A camera records a live video stream, from which a snapshot is taken with the help of interface. The system is trained for each type of count hand gestures (one, two, three, four, and five) at least once. After that a test gesture is given to it and the system tries to recognize it.A research was carried out on a number of algorithms that could best differentiate a hand gesture. It was found that the diagonal sum algorithm gave the highest accuracy rate. In the preprocessing phase, a self-developed algori

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Glatt, Ruben [UNESP]. "Deep learning architecture for gesture recognition." Universidade Estadual Paulista (UNESP), 2014. http://hdl.handle.net/11449/115718.

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Made available in DSpace on 2015-03-03T11:52:29Z (GMT). No. of bitstreams: 0 Previous issue date: 2014-07-25Bitstream added on 2015-03-03T12:06:38Z : No. of bitstreams: 1 000807195.pdf: 2462524 bytes, checksum: 91686fbe11c74337c40fe57671eb8d82 (MD5)<br>O reconhecimento de atividade de visão de computador desempenha um papel importante na investigação para aplicações como interfaces humanas de computador, ambientes inteligentes, vigilância ou sistemas médicos. Neste trabalho, é proposto um sistema de reconhecimento de gestos com base em uma arquitetura de aprendizagem profunda. Ele é usado pa

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Gillian, N. E. "Gesture recognition for musician computer interaction." Thesis, Queen's University Belfast, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.546348.

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Cairns, Alistair Y. "Towards the automatic recognition of gesture." Thesis, University of Dundee, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.385803.

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Harding, Peter Reginald George. "Gesture recognition by Fourier analysis techniques." Thesis, City University London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440735.

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Tanguay, Donald O. (Donald Ovila). "Hidden Markov models for gesture recognition." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/37796.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.<br>Includes bibliographical references (p. 41-42).<br>by Donald O. Tanguay, Jr.<br>M.Eng.

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16

Yao, Yi. "Hand gesture recognition in uncontrolled environments." Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/74268/.

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Human Computer Interaction has been relying on mechanical devices to feed information into computers with low efficiency for a long time. With the recent developments in image processing and machine learning methods, the computer vision community is ready to develop the next generation of Human Computer Interaction methods, including Hand Gesture Recognition methods. A comprehensive Hand Gesture Recognition based semantic level Human Computer Interaction framework for uncontrolled environments is proposed in this thesis. The framework contains novel methods for Hand Posture Recognition, Hand G

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Glatt, Ruben. "Deep learning architecture for gesture recognition /." Guaratinguetá, 2014. http://hdl.handle.net/11449/115718.

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Orientador: José Celso Freire Junior<br>Coorientador: Daniel Julien Barros da Silva Sampaio<br>Banca: Galeno José de Sena<br>Banca: Luiz de Siqueira Martins Filho<br>Resumo: O reconhecimento de atividade de visão de computador desempenha um papel importante na investigação para aplicações como interfaces humanas de computador, ambientes inteligentes, vigilância ou sistemas médicos. Neste trabalho, é proposto um sistema de reconhecimento de gestos com base em uma arquitetura de aprendizagem profunda. Ele é usado para analisar o desempenho quando treinado com os dados de entrada multi-modais em

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Caceres, Carlos Antonio. "Machine Learning Techniques for Gesture Recognition." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/52556.

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Classification of human movement is a large field of interest to Human-Machine Interface researchers. The reason for this lies in the large emphasis humans place on gestures while communicating with each other and while interacting with machines. Such gestures can be digitized in a number of ways, including both passive methods, such as cameras, and active methods, such as wearable sensors. While passive methods might be the ideal, they are not always feasible, especially when dealing in unstructured environments. Instead, wearable sensors have gained interest as a method of gesture classifica

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Pfister, Tomas. "Advancing human pose and gesture recognition." Thesis, University of Oxford, 2015. http://ora.ox.ac.uk/objects/uuid:64e5b1be-231e-49ed-b385-e87db6dbeed8.

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This thesis presents new methods in two closely related areas of computer vision: human pose estimation, and gesture recognition in videos. In human pose estimation, we show that random forests can be used to estimate human pose in monocular videos. To this end, we propose a co-segmentation algorithm for segmenting humans out of videos, and an evaluator that predicts whether the estimated poses are correct or not. We further extend this pose estimator to new domains (with a transfer learning approach), and enhance its predictions by predicting the joint positions sequentially (rather than inde

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Al-Rajab, Moaath. "Hand gesture recognition for multimedia applications." Thesis, University of Leeds, 2008. http://etheses.whiterose.ac.uk/607/.

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Hand gesture is potentially a very natural and useful modality for human-machine interaction. It is considered to be one of the most complicated and interesting challenges in computer vision due to its articulated structure and environmental variations. Solving such challenges requires robust hand detection, feature description, and viewpoint invariant classification. This thesis introduces several steps to tackle these challenges and applies them in a hand-gesture-based application (a game) to demonstrate the proposed approach. Techniques on new feature description, hand gesture detection and

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Jia, Jia. "Interactive Imaging via Hand Gesture Recognition." Thesis, University of Bradford, 2009. http://hdl.handle.net/10454/4259.

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With the growth of computer power, Digital Image Processing plays a more and more important role in the modern world, including the field of industry, medical, communications, spaceflight technology etc. As a sub-field, Interactive Image Processing emphasizes particularly on the communications between machine and human. The basic flowchart is definition of object, analysis and training phase, recognition and feedback. Generally speaking, the core issue is how we define the interesting object and track them more accurately in order to complete the interaction process successfully. This thesis

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Toure, Zikra. "Human-Machine Interface Using Facial Gesture Recognition." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc1062841/.

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This Master thesis proposes a human-computer interface for individual with limited hand movements that incorporate the use of facial gesture as a means of communication. The system recognizes faces and extracts facial gestures to map them into Morse code that would be translated in English in real time. The system is implemented on a MACBOOK computer using Python software, OpenCV library, and Dlib library. The system is tested by 6 students. Five of the testers were not familiar with Morse code. They performed the experiments in an average of 90 seconds. One of the tester was familiar with Mor

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Liu, Nianjun. "Hand gesture recognition by Hidden Markov Models /." [St. Lucia, Qld.], 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18158.pdf.

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24

Pun, James Chi-Him. "Gesture recognition with application in music arrangement." Diss., University of Pretoria, 2006. http://upetd.up.ac.za/thesis/available/etd-11052007-171910/.

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25

Chan, Siu Chi 1979. "Hand and fingertip tracking for gesture recognition." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=83855.

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A hand gesture interface allows for seamless interaction with both virtual and physical objects in computer augmented environments. However, developing a reliable hand-pose detection and recognition system using computer vision remain to be a challenging problem. In this thesis, two tracking systems relying on different image features are described and compared. The first system employs skin color to extract skin regions from an image. Then, a user's hand is located by using a circle fitting algorithms inside the largest skin blob. To find fingertips, a circular Hough transform is appli

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Kolesnik, Paul. "Conducting gesture recognition, analysis and performance system." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=81499.

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A number of conducting gesture analysis and performance systems have been developed over the years. However, most of the previous projects either primarily concentrated on tracking tempo and amplitude indicating gestures, or implemented individual mapping techniques for expressive gestures that varied from research to research. There is a clear need for a uniform process that could be applied toward analysis of both indicative and expressive gestures. The proposed system provides a set of tools that contain extensive functionality for identification, classification and performance with

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King, Rachel C. "Hand gesture recognition for minimally invasive surgery." Thesis, Imperial College London, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.497748.

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Puranam, Muthukumar B. "Towards Full-Body Gesture Analysis and Recognition." UKnowledge, 2005. http://uknowledge.uky.edu/gradschool_theses/227.

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With computers being embedded in every walk of our life, there is an increasing demand forintuitive devices for human-computer interaction. As human beings use gestures as importantmeans of communication, devices based on gesture recognition systems will be effective for humaninteraction with computers. However, it is very important to keep such a system as non-intrusive aspossible, to reduce the limitations of interactions. Designing such non-intrusive, intuitive, camerabasedreal-time gesture recognition system has been an active area of research research in the fieldof computer vision.Gestur

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Zanghieri, Marcello. "sEMG-based hand gesture recognition with deep learning." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18112/.

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Hand gesture recognition based on surface electromyographic (sEMG) signals is a promising approach for the development of Human-Machine Interfaces (HMIs) with a natural control, such as intuitive robot interfaces or poly-articulated prostheses. However, real-world applications are limited by reliability problems due to motion artifacts, postural and temporal variability, and sensor re-positioning. This master thesis is the first application of deep learning on the Unibo-INAIL dataset, the first public sEMG dataset exploring the variability between subjects, sessions and arm postures, by colle

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Bernard, Arnaud Jean Marc. "Human computer interface based on hand gesture recognition." Thesis, Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/42748.

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With the improvement of multimedia technologies such as broadband-enabled HDTV, video on demand and internet TV, the computer and the TV are merging to become a single device. Moreover the previously cited technologies as well as DVD or Blu-ray can provide menu navigation and interactive content. The growing interest in video conferencing led to the integration of the webcam in different devices such as laptop, cell phones and even the TV set. Our approach is to directly use an embedded webcam to remotely control a TV set using hand gestures. Using specific gestures, a user is able to control

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Zhu, Hong Min. "Real-time hand gesture recognition using motion tracking." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2182870.

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Wilson, Andrew David. "Adaptive models for the recognition of human gesture." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/62951.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2000.<br>Includes bibliographical references (leaves 135-140).<br>Tomorrow's ubiquitous computing environments will go beyond the keyboard, mouse and monitor paradigm of interaction and will require the automatic interpretation of human motion using a variety of sensors including video cameras. I present several techniques for human motion recognition that are inspired by observations on human gesture, the class of communicative human movement. Typically, gesture reco

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Moy, Milyn C. (Milyn Cecilia) 1975. "Real-time hand gesture recognition in complex environments." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/50054.

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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.<br>Includes bibliographical references (leaves 65-68).<br>by Milyn C. Moy.<br>S.B.and M.Eng.

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Bailey, Sam. "Interactive exploration of historic information via gesture recognition." Thesis, University of East Anglia, 2012. https://ueaeprints.uea.ac.uk/42540/.

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Developers of interactive exhibits often struggle to �nd appropriate input devices that enable intuitive control, permitting the visitors to engage e�ectively with the content. Recently motion sensing input devices like the Microsoft Kinect or Panasonic D-Imager have become available enabling gesture based control of computer systems. These devices present an attractive input device for exhibits since the user can interact with their hands and they are not required to physically touch any part of the system. In this thesis we investigate techniques to enable the raw data coming from these type

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李世淵. "Anti-Gesture Model For Gesture Recognition." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/88514897535275004323.

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Tsai, Jui-Che, and 蔡睿哲. "Hand Gesture Recognition." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/e6nbcb.

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碩士<br>亞東技術學院<br>資訊與通訊工程研究所<br>100<br>In recent years, image processing has been developed for a long time. Hand recognition systems attract many researchers. In this paper, using a easy hand gesture recognition algorithm reduces the amount of data and obtains the desired result. First of all, the computer gets two pictures by a webcam we set up. The resolution of pictures are set as 320*240. The background subtraction method from two pictures is used to reduce the amount of data. Then, erosion and dilation methods are used to reduce the noise. The remaining image is only the hand region. Then

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Lemarcis, Baptiste. "Towards streaming gesture recognition." Thèse, 2016. http://constellation.uqac.ca/4132/1/Lemarcis_uqac_0862N_10294.pdf.

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The emergence of low-cost sensors allows more devices to be equipped with various types of sensors. In this way, mobile device such as smartphones or smartwatches now may contain accelerometers, gyroscopes, etc. This offers new possibilities for interacting with the environment and benefits would come to exploit these sensors. As a consequence, the literature on gesture recognition systems that employ such sensors grow considerably. The literature regarding online gesture recognition counts many methods based on Dynamic Time Warping (DTW). However, this method was demonstrated has non-efficien

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Sahoo, Lagnajeet. "Hand Gesture Recognition System." Thesis, 2015. http://ethesis.nitrkl.ac.in/7739/1/602.pdf.

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Hand Gesture Recognition is a well-researched topic in the community of Machine Learning, Computer Graphics and Image Processing. The system which are based on Recognition technology follow mathematically rich and complicated algorithms whose main aim is to teach a computer different gestures. Because there are very large sets of gestures, the number of methodologies to identify the set of gestures is also large. In this thesis, I have concentrated on the gestures are based on hands. The thesis is divided into two sections namely: Static mode and Dynamic. The Static mode concentrates on gestur

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Pradhan, Lalit Mohan. "Gesture Based Character Recognition." Thesis, 2015. http://ethesis.nitrkl.ac.in/7806/1/2015_Gesture_Pradhan.pdf.

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Gesture is rudimentary movements of a human body part, which depicting the important movement of an individual. It is high significance for designing efficient human-computer interface. An proposed method for Recognition of character(English alphabets) from gesture i.e gesture is performed by the utilization of a pointer having color tip (is red, green, or blue). The color tip is segment from back ground by converting RGB to HSI color model. Motion of color tip is identified by optical flow method. During formation of multiple gesture the unwanted lines are removed by optical flow method. The

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Wu, Zong-Guei, and 吳宗桂. "Using KINECT Gesture Recognition for User Recognition." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/qau9uf.

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碩士<br>國立虎尾科技大學<br>電機工程研究所<br>103<br>In recent years, the safe identification system used in intelligent environment has been attractive by people and more and more similarly systems were proposed. This paper presented a user identification based on posture and combined the skeleton data which gets from KINECT. It contains two types of features, including non-learning features and learning features of the learning methods. Based on human skeleton joints, there are three user features proposed by the author. The methods in sequence are “Adjacency Joint Distance”, “Confirm Skeleton Angle” and the

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Chen, Chih-Yu, and 陳治宇. "Virtual Mouse：Vision-Based Gesture Recognition." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/74539959450046293234.

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碩士<br>國立中山大學<br>資訊工程學系研究所<br>91<br>The thesis describes a method for human-computer interaction through vision-based gesture recognition and hand tracking, which consists of five phases: image grabbing, image segmentation, feature extraction, gesture recognition, and system mouse controlling. Unlike most of previous works, our method recognizes hand with just one camera and requires no color markers or mechanical gloves. The primary work of the thesis is improving the accuracy and speed of the gesture recognition. Further, the gesture commands will be used to replace the mouse interface on

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TIWARI, MANU, and 馬麗麗. "Gesture Recognition in Shopping Scenario." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/q8edw2.

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碩士<br>國立交通大學<br>電機資訊國際學程<br>107<br>Smart phones and Smart wristbands are being used for effective activity recognition for health management, personal identification, payment purposes etc. The shopping industry is not far behind in experimenting with these devices in order to make shopping experience better for customers, gaining more information on their behavior, benefiting businesses etc. This work here aims at recognizing activities performed during shopping using an inertial sensor. The study of segments generated and processed to develop a recognition model. The model is robust and light

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Mandal, Itishree, and Samiksha Ray. "Hand gesture based digit recognition." Thesis, 2014. http://ethesis.nitrkl.ac.in/6488/1/E-30.pdf.

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Recognition of static hand gestures in our daily plays an important role in human-computer interaction. Hand gesture recognition has been a challenging task now a days so a lot of research topic has been going on due to its increased demands in human computer interaction. Since Hand gestures have been the most natural communication medium among human being, so this facilitate efficient human computer interaction in many electronics gazettes . This has led us to take up this task of hand gesture recognition. In this project different hand gestures are recognized and no of fingers are counted. R

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Chen, Jiunn-Yeuo, and 陳俊有. "Hand Gesture Commands for a PC Presentation:Hand Gesture Recognition andPointing Computation." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/64517050729864669654.

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碩士<br>國立交通大學<br>資訊工程學系<br>85<br>In a PC presentation system, speakers must bow to control the mouse or keyboard key to move the screen upward, downward, leftward, rightward.This causes the time delay or interrupt of presentation. In this thesis, we want to remove this drawback. We use human gestures to replace the mouse function in the PC presentation system.We have eight hand gestures including up, down, left, right, zoom in, zoom out, hold and point. With two calibrated TV cameras, we cap

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Chen, Feng-Sheng, and 陳豐生. "Gesture Recognition Using Hidden Markov Models." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/39515573353219025950.

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碩士<br>國立清華大學<br>電機工程學系<br>87<br>In this thesis, we introduce a hand gesture recognition system to recognize continuous gesture in simple background. The system consists of three modules: feature extraction, hidden Markov model (HMM) training, and gesture recognition using the HMMs. First, we apply the motion information to extract the hand-shape and apply the scale and rotation-invariant Fourier descriptor to characterize hand figures. Then we combine Fourier descriptor and motion information of input image sequence as our feature vector. After having extracted the feature vector, we first tra

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Chen, Kuan-Wei, and 陳冠緯. "Gesture recognition of smart mobile device." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/62wfvm.

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碩士<br>樹德科技大學<br>資訊工程系碩士班<br>104<br>With technology advancements, today’s smart mobile devices are moving towards increasingly higher performance specifications. This thesis puts the neural network training that could only be run on home computers or higher level devices in the past to run on today’s smart mobile devices. For the purpose of this thesis, a system was designed on an Android smart mobile device. Acceleration values were obtained using the existing gravitational acceleration sensor in the device and finite state capture and then went through average filtering and normalization befo

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Chao-Hui, Huang, and 黃朝暉. "Silhouette-Based Hand Gesture Recognition System." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/93267423724812911907.

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碩士<br>中華大學<br>資訊工程學系碩士班<br>89<br>Let computer science taking over some jobs of human is a dream. However, Duplicating of human intuition is very difficult. In this paper, we try to duplicate the vision of human intuition, and present that by human hand gesture recognition with low computation requirement. Usually, the human hand gesture recognition system requires either high cost of computation, or special auxiliary devices. Due to this, a faster and convenient method becomes necessary. For the sake of real-time implementation, we developed two main algorithms: Curve Detection Algorithm (CDA)

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AlSharif, Mohammed H. "Hand Gesture Recognition Using Ultrasonic Waves." Thesis, 2016. http://hdl.handle.net/10754/609434.

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Gesturing is a natural way of communication between people and is used in our everyday conversations. Hand gesture recognition systems are used in many applications in a wide variety of fields, such as mobile phone applications, smart TVs, video gaming, etc. With the advances in human-computer interaction technology, gesture recognition is becoming an active research area. There are two types of devices to detect gestures; contact based devices and contactless devices. Using ultrasonic waves for determining gestures is one of the ways that is employed in contactless devices. Hand gesture reco

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Brás, André Filipe Pereira. "Gesture recognition using deep neural networks." Master's thesis, 2017. http://hdl.handle.net/10316/83023.

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Dissertação de Mestrado Integrado em Engenharia Mecânica apresentada à Faculdade de Ciências e Tecnologia<br>Esta dissertação teve como principal objetivo o desenvolvimento de um método para realizar segmentação e reconhecimento de gestos. A pesquisa foi motivada pela importância do reconhecimento de ações e gestos humanos em aplicações do mundo real, como a Interação Homem-Máquina e a compreensão de linguagem gestual. Além disso, pensa-se que o estado da arte atual pode ser melhorado, já que esta é uma área de pesquisa em desenvolvimento contínuo, com novos métodos e ideias surgindo frequente

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TSAI, HU-CHUNG, and 蔡鵠仲. "Research on Gesture Recognition Controlled Quadcopter." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/24984313688431062793.

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碩士<br>國立高雄海洋科技大學<br>輪機工程研究所<br>104<br>In this thesis, control methods analysis and design for quadcopter are considered. A human–machine interface of gesture recognition is developed to control the quadcopter. The main system architecture includes the quadcopter, the synchronous attitude simulation system, the proportional-integral-derivative (PID) controller, and a human-machine interface of gesture recognition. The quadcopter mechanism is designed in size 330mm*330mm with X-shaped configuration of the motor structure. Synchronous attitude simulation system is mainly used to obtain the quadco

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