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Dissertations / Theses on the topic 'Vision Based Gesture Recognition'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Akremi, Mohamed. "Manifold-Based Approaches for Action and Gesture Recognition." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPAST045.

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La reconnaissance des actions humaines (HAR) est devenue un domaine de recherche essentiel en raison de ses nombreuses applications dans le monde réel, notamment l'interaction homme-machine, la santé intelligente, la réalité virtuelle, la surveillance, le contrôle des drones (UAV) et les systèmes autonomes. Au cours des dernières décennies, de nombreuses approches ont été développées pour reconnaître les actions humaines à partir de séquences vidéo RGB monoculaires. Plus récemment, l'émergence des capteurs de profondeur a favorisé le développement de l'analyse des activités en 3D et de la reco

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Crawford, Gordon Finlay. "Vision-based analysis, interpretation and segmentation of hand shape using six key marker points." Thesis, University of Ulster, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.243732.

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3

Fritsch, Jan Nikolaus. "Vision based recognition of gestures with context." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=968577474.

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4

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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Mazhar, Osama. "Vision-based human gestures recognition for human-robot interaction." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTS044.

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Dans la perspective des usines du futur, pour garantir une interaction productive, sure et efficace entre l’homme et le robot, il est impératif que le robot puisse interpréter l’information fournie par le collaborateur humain. Pour traiter cette problématique nous avons exploré des solutions basées sur l’apprentissage profond et avons développé un framework pour la détection de gestes humains. Le framework proposé permet une détection robuste des gestes statiques de la main et des gestes dynamiques de la partie supérieure du corps.Pour la détection des gestes statiques de la main, openpose est

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Hettiarachchi, Randima. "Multi-Manifold learning and Voronoi region-based segmentation with an application in hand gesture recognition." Elsevier, 2015. http://hdl.handle.net/1993/31969.

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A computer vision system consists of many stages, depending on its application. Feature extraction and segmentation are two key stages of a typical computer vision system and hence developments in feature extraction and segmentation are significant in improving the overall performance of a computer vision system. There are many inherent problems associated with feature extraction and segmentation processes of a computer vision system. In this thesis, I propose novel solutions to some of these problems in feature extraction and segmentation. First, I explore manifold learning, which is a no

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Blonski, Brian M. "THE USE OF CONTEXTUAL CLUES IN REDUCING FALSE POSITIVES IN AN EFFICIENT VISION-BASED HEAD GESTURE RECOGNITION SYSTEM." DigitalCommons@CalPoly, 2010. https://digitalcommons.calpoly.edu/theses/295.

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This thesis explores the use of head gesture recognition as an intuitive interface for computer interaction. This research presents a novel vision-based head gesture recognition system which utilizes contextual clues to reduce false positives. The system is used as a computer interface for answering dialog boxes. This work seeks to validate similar research, but focuses on using more efficient techniques using everyday hardware. A survey of image processing techniques for recognizing and tracking facial features is presented along with a comparison of several methods for tracking and ident

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Lam, Benny, and Jakob Nilsson. "Creating Good User Experience in a Hand-Gesture-Based Augmented Reality Game." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-156878.

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The dissemination of new innovative technology requires feasibility and simplicity. The problem with marker-based augmented reality is similar to glove-based hand gesture recognition: they both require an additional component to function. This thesis investigates the possibility of combining markerless augmented reality together with appearance-based hand gesture recognition by implementing a game with good user experience. The methods employed in this research consist of a game implementation and a pre-study meant for measuring interactive accuracy and precision, and for deciding upon which g

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9

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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10

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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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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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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13

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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14

Liu, X. (Xin). "Human motion detection and gesture recognition using computer vision methods." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526222011.

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Abstract Gestures are present in most daily human activities and automatic gestures analysis is a significant topic with the goal of enabling the interaction between humans and computers as natural as the communication between humans. From a computer vision perspective, a gesture analysis system is typically composed of two stages, the low-level stage for human motion detection and the high-level stage for understanding human gestures. Therefore, this thesis contributes to the research on gesture analysis from two aspects, 1) Detection: human motion segmentation from video sequences, and 2) Un

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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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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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Huang, Yu. "Hand gesture recognition methods based on concept learning." Thesis, University of Wales Trinity Saint David, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667760.

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18

Yuan, Yu. "Image-based gesture recognition with support vector machines." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 155 p, 2008. http://proquest.umi.com/pqdweb?did=1601517921&sid=2&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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Simonsson, Huck Andreas. "Exploring gesture based interaction and visualizations for supporting collaboration." Thesis, Linnéuniversitetet, Institutionen för datavetenskap, fysik och matematik, DFM, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-12896.

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This thesis will introduce the concept of collaboratively using freehand gestures to interact with visualizations. It could be problematic to work with data and visualizations together with others in the traditional desktop setting because of the limited screen size and a single user input device. Therefore this thesis suggests a solution by integrating computer vision and gestures with interactive visualizations. This integration resulted in a prototype where multiple users can interact with the same visualizations simultaneously. The prototype was evaluated and tested on ten potential users.

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Gonzalez, Preciado Matilde. "Computer vision methods for unconstrained gesture recognition in the context of sign language annotation." Toulouse 3, 2012. http://thesesups.ups-tlse.fr/1798/.

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Cette thèse porte sur l'étude des méthodes de vision par ordinateur pour la reconnaissance de gestes naturels dans le contexte de l'annotation de la Langue des Signes. La langue des signes (LS) est une langue gestuelle développée par les sourds pour communiquer. Un énoncé en LS consiste en une séquence de signes réalisés par les mains, accompagnés d'expressions du visage et de mouvements du haut du corps, permettant de transmettre des informations en parallèles dans le discours. Même si les signes sont définis dans des dictionnaires, on trouve une très grande variabilité liée au contexte lors

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Mekala, Priyanka. "Field Programmable Gate Array Based Target Detection and Gesture Recognition." FIU Digital Commons, 2012. http://digitalcommons.fiu.edu/etd/723.

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The move from Standard Definition (SD) to High Definition (HD) represents a six times increases in data, which needs to be processed. With expanding resolutions and evolving compression, there is a need for high performance with flexible architectures to allow for quick upgrade ability. The technology advances in image display resolutions, advanced compression techniques, and video intelligence. Software implementation of these systems can attain accuracy with tradeoffs among processing performance (to achieve specified frame rates, working on large image data sets), power and cost constraints

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Lai, Yun-Chien, and 賴韻芊. "A Computer-Vision Based Gesture Recognition System." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/20550549557880099745.

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碩士<br>國立臺灣大學<br>資訊網路與多媒體研究所<br>97<br>This paper presents a new approach to 3D model-based gesture recognition for controlling multimedia player. The motivation of this paper is to make home appliance aware of user’s intention. This 3D model-based gesture recognition system adopts a Bayesian framework to track the user’s hand posture and to recognize meaning of these postures for controlling 3D player interactively. To avoid the high dimensionality of the whole 3D upper body model, which may complicate the gesture tracking problem, our system applies a new hierarchical tracking algorithm to imp

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Chang, Kuo-Jun, and 張國君. "Computer Vision Based Hand Gesture Recognition System." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/51191244799518697469.

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Hsu, Ying-shan, and 徐瑩珊. "Continuous 3D Gesture Recognition Based on Stereo Vision." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/60022886516784584160.

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碩士<br>國立中央大學<br>資訊工程研究所<br>98<br>In vision-based human-computer interaction system, hand region is usually the nearest object to cameras, therefore, it is effective to detect hand region by 3D information. We use Particle Swarm Optimization (PSO) algorithm to enhance the stability and robustness of continuous image hand region detection. This paper proposes a dual modal dynamic gesture recognition method. The first one (MIP) consists of motion history image (MHI), image moment feature extraction and probability neural network (PNN), the second one (FIS) is the fuzzy inference system based on t

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Wu, Chen-Hao, and 吳振豪. "Vision Based Hand Gesture Recognition in Cluttered Backgrounds." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/25796162095989573012.

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碩士<br>國立臺灣大學<br>電機工程學研究所<br>103<br>A robust algorithm capable of segmenting specified hand gestures in cluttered image sequences is proposed. Typically, vision-based gesture recognition systems suffer from the difficulty of hand region segmentation, which includes the change of lighting conditions, the presence of other skin color objects and the movement of background objects. The main concern of this paper is to design an algorithm for RGB camera that locates hand region correctly even under complex backgrounds. The proposed segmentation algorithm, thumb-cover detection algorithm, restricts

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Hsieh, Min-Ting, and 謝旻廷. "Handwriting Pen Gesture Recognition Based on Computer Vision." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/71842083726352985367.

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碩士<br>元智大學<br>通訊工程學系<br>98<br>This thesis presents a handwriting pen gesture recognition system. The system recognizes handwriting pen gestures based on computer vision techniques. The fingertip writing trajectory of user is extracted from the video by image processing. After detecting the trajectory, the bending points are detected by angle calculating and kernel density estimation. The pen gesture trajectory is separated into sub-strokes according to the bending points. Then, a feature sequence is extracted from each sub-stroke. This system adopts the best clustering index and clustering alg

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Jyun-SiangFan and 范鈞翔. "Study on Vision-Based Static Hand Gesture Recognition." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/fazwg7.

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Huang, Shin-zung, and 黃信榮. "Human-Machine Interaction Using Stereo Vision-based Gesture Recognition." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/89650789224703404252.

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碩士<br>國立中央大學<br>資訊工程研究所<br>97<br>At present, the development of consumer electronic products focuses on more convenient and friendly interactive interface. Through the body posture interacting with machine without direct touch has become an important research trend. This paper presents a stereo vision-based gesture recognition system of human-computer interaction. Two cameras are set on the computer screen, and the Lens Shooting is in front of screen. Assuming the hand which controls the computer is the nearest object to the screen. We use the neural network to achieve the mapping model of abe

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Wang, Cheng-Chieh, and 王政傑. "Vision-Based Human Gesture Recognition for a Demonstration System." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/54676760151896354820.

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碩士<br>銘傳大學<br>資訊傳播工程學系碩士班<br>99<br>With the rapid growing of human computer interaction devices, the research on the vision-based human gesture recognition has received wide attention recently. However, it still faces two main challenges: (a) real-time processing and (b) robustness to the various environmental conditions including lighting variations, hand’s complexity, background artifacts, and user differences. In this thesis, we propose a posture/gesture recognition method, which can operate in real-time for demonstration purpose. This method consists of four main units: start gesture dete

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Ghosh, Dipak Kumar. "A Framework for Vision-based Static Hand Gesture Recognition." Thesis, 2016. http://ethesis.nitrkl.ac.in/8052/1/2016_510EC106_Dipak_k_Ghosh_Framework.pdf.

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In today’s technical world, the intellectual computing of a efficient human-computer interaction (HCI) or human alternative and augmentative communication (HAAC) is essential in our lives. Hand gesture recognition is one of the most important techniques that can be used to build up a gesture based interface system for HCI or HAAC application. Therefore, suitable development of gesture recognition method is necessary to design advance hand gesture recognition system for successful applications like robotics, assistive systems, sign language communication, virtual reality etc. However, the varia

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Reddy, Dandu Amarnatha. "Vision Based Hand Gesture Recognition for Human Computer Interaction." Thesis, 2018. http://ethesis.nitrkl.ac.in/9978/1/2018_MT_216EC6254_DAReddy_Vision.pdf.

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The hand gesture recognition system is widely used in the development of human-machine interaction. The vision-based hand gesture recognition is achieved by the following steps: preprocessing, feature extraction and classification. The aim of preprocessing stage is to localize the hand region from the image frame. The Laplacian of Gaussian filtering technique along with zero crossing detector is applied on hand gesture images to detect the edges of hand region. This work proposes a novel feature extraction technique, which is based on local histogram feature descriptor (LHFD). The proposed fea

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Wu, Wen-Chin, and 吳玟槿. "Computer Vision-Based Hand Gesture Recognition for Human-Robot Interactions." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/qnqd5m.

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碩士<br>國立臺北科技大學<br>電機工程系所<br>99<br>This thesis focuses on the research of human hand gesture detection and recognition for the indoor surveillance system, which is capable of interacting with a mobile robot. Through recognizing human hand gesture, the developed system can direct the robot to carry out various actions. In the strategy of hand gesture detection, the original image is transformed to YCbCr color space and the subspace of human skin color in the face and hands can then be segmented. By means of the posture feature of human body, the fuzzy segment model is designed to identify the ha

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Liao, Chung-ju, and 廖崇儒. "Vision-based hand gesture recognition system for users on wheelchairs." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/50702407836241470709.

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碩士<br>國立臺灣科技大學<br>電機工程系<br>98<br>In this study, a hand gesture recognition system is proposed for users on wheelchairs. Unlike other studies that focus on the stage of hand gesture recognition, many problems are considered, such as detection of when a hand reaches in the field of the camera view or detection of a full palm. There are 4 stages in the proposed system, detection of the appearance of hands, segmentation of hand regions, detection of full palm and hand gesture recognition. Detection of the appearance of hands is to find out when a hand appears in the front of the camera. The hand r

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Liu, Ming-Shan, and 劉明山. "A Study on Vision-Based Hand Tracking and Gesture Recognition." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/14638549661509171398.

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碩士<br>國立成功大學<br>電機工程學系碩博士班<br>97<br>Nowadays, most of human computer interface (HCI) use the keyboard or mouse as the command input device. However, gesture is considered one of the most natural ways for human to communicate with other people or to issue commands. Generally, the gesture recognition system is designed based on computer vision to automatically detect/track human hands and also recognize the gesture. In object detection and tracking, this thesis develops a multi-cue similarity measurement algorithm for hand detection, and use an object based method to continuously track the hand.

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O'Hagan, Rochelle G. "Vision-based gesture recognition as an interface to virtual environments." Phd thesis, 2002. http://hdl.handle.net/1885/148650.

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Sharma, Mrityunjay, and Prabir Kumar Choudhury. "Gesture Recognition Based on Computer Vision on a Standalone System." Thesis, 2015. http://ethesis.nitrkl.ac.in/7807/1/2015_Gesture_Sharma.pdf.

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Our project uses computer vision methods gesture recognition in which a camera interfaced to a system captures real time images and after further processing able to recognize the gesture shown to be interpreted. Our project mainly aims at hand gestures and after extracting information we try to produce it as an audio or in some visual form. We have used adaptive background subtraction with Haar classifiers to implement segmentation then we used convex hull and convex defects along with other feature extraction algorithms to interpret the gesture. First, this is implemented on a PC or laptop an

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Chung-Yang, Hsieh, and 謝中揚. "A Study on Vision-based Human Action and Hand Gesture Recognition." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/ws4zza.

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博士<br>國立中正大學<br>資訊工程研究所<br>104<br>In this dissertation, we develop three systems for gesture and action recognition. First system uses the trajectory of hand motion as the datum source for sign language classification and retrieval. In this system, a trajectory is ﬁrstly projected by the Kernel Principal Component Analysis (KPCA) which can be considered as an implicit mapping to a much higher-dimensional feature space. The high dimensionality can effectively improve the accuracy in recognizing motion trajectories. Then, Nonparametric Discriminant Analysis (NDA) is used to extract the most disc

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Tseng, Yu-Lin, and 曾鈺琳. "A 2D Controlling Interface Based on the Double-Handed Computer Vision Gesture Recognition." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/qrt5xr.

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碩士<br>國立臺北科技大學<br>創新設計研究所<br>100<br>The Movie “Minority Report” brought out a whole new concept of human computer technology, which has been evoking numerous related researches ever since. The evolution of input devices began with keyboards. There then ensued the invention of “mouse cursors”. Since that decade, multi-touch devices have been all the rage. Thus, more and more HCI technologies have been developed by researchers. According to the related studies, we learnt that there are still technical and conceptual obstacles existing in the recognition process. Hence, we reevaluate the rel

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Yao, Hong-Lin, and 姚宏霖. "NI-Vision-Based Hand Gesture Recognition Applying to an AX-12 Robot Arm." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/49036731411766519887.

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碩士<br>國立勤益科技大學<br>機械工程系<br>102<br>This research applied a 4-DOF robot arm, which is assembled with the AX-12 intelligent servo motors manufactured by ROBOTICS Inc. Based on the Inverse Kinematics, the rotation angles of the motors were calculated to move the arm to the target precisely. This research introduces the Android system combined with the NI (National Instrument) vision system for image recognition. A self-defined hand gesture was used to control the closure of the gripper which is located at the end of the robot arm. To response with the varieties of different environments during the

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Ching-Yu, Chien. "Vision-based Real-time Pointing Arm Gesture Tracking and Recognition System using Multiple Cameras." 2006. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0016-0109200613415356.

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Chien, Ching-Yu, and 簡敬宇. "Vision-based Real-time Pointing Arm Gesture Tracking and Recognition System using Multiple Cameras." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/84402742103207006919.

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碩士<br>國立清華大學<br>電機工程學系<br>94<br>In this thesis, we develop a real-time arm pointing system. The main contribution of the system is using three cameras to track the pointing arm and identify several pointing targets in 3-D space. The system allows the user to make the arm pointing and the walking in a work space at the same time. The novelty of our method is directly tracking two 3-D points representing the pointing line in 3-D space and then refining the tracking results. We take advantages of Direct Linear Transformation (DLT) to extend the samples of particle filter to 3-D space. In our syst

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Li, Zhe [Verfasser]. "Vision-based manipulative gesture recognition in a human-robot interaction scenario / vorgelegt von Zhe Li." 2008. http://d-nb.info/991569105/34.

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Trigueiros, Paulo José de Albuquerque Cardoso. "Hand gesture recognition system based in computer vision and machine learning: Applications on human-machine interaction." Doctoral thesis, 2014. http://hdl.handle.net/1822/40407.

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Tese de Doutoramento em Engenharia de Eletrónica e de Computadores<br>Sendo uma forma natural de interação homem-máquina, o reconhecimento de gestos implica uma forte componente de investigação em áreas como a visão por computador e a aprendizagem computacional. O reconhecimento gestual é uma área com aplicações muito diversas, fornecendo aos utilizadores uma forma mais natural e mais simples de comunicar com sistemas baseados em computador, sem a necessidade de utilização de dispositivos extras. Assim, o objectivo principal da investigação na área de reconhecimento de gestos aplicada à

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Fritsch, Jan Nikolaus [Verfasser]. "Vision based recognition of gestures with context / vorgelegt von Jan Nikolaus Fritsch." 2003. http://d-nb.info/968577474/34.

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Krüger, Maximilian [Verfasser]. "Vision based tracking and recognition of dynamic hand gestures / vorgelegt von Maximilian Krüger." 2007. http://d-nb.info/98738449X/34.

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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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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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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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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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Liu, Shu-ming, and 劉書銘. "Depth-based Loose Static Gesture Recognition." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/99533363836421368543.

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碩士<br>國立中央大學<br>資訊工程學系<br>101<br>In recent year, gesture recognition is an important issue in the field of human computer interaction. The most commonly used applications include game control, home appliances control, robot control, etc. Moreover, due to the effect of lighting, complex backgrounds and the restricted standard gestures without curvature of the fingers, some gesture recognition methods systems are neither intuitive nor comfortable for users. Thus, a loose gesture recognition system against lighting and complex backgrounds is needed. The purpose of this thesis is to develop a

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