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Relevant bibliographies by topics / Face detection / Dissertations / Theses

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Dissertations / Theses on the topic 'Face detection'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Espinosa-Romero, Arturo. "Situated face detection." Thesis, University of Edinburgh, 2001. http://hdl.handle.net/1842/6667.

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In the last twenty years, important advances have been made in the field of automatic face processing, given the importance of human faces for personal identification, emotional expression and verbal and non verbal communication. The very first step in a face processing algorithm is the detection of faces; while this is a trivial problem in controlled environments, the detection of faces in real environments is still a challenging task. Until now, the most successful approaches for face detection represent the face as a grey-level pattern, and the problem itself is considered as the classifica

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2

Mäkelä, J. (Jussi). "GPU accelerated face detection." Master's thesis, University of Oulu, 2013. http://urn.fi/URN:NBN:fi:oulu-201303181103.

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Graphics processing units have massive parallel processing capabilities, and there is a growing interest in utilizing them for generic computing. One area of interest is computationally heavy computer vision algorithms, such as face detection and recognition. Face detection is used in a variety of applications, for example the autofocus on cameras, face and emotion recognition, and access control. In this thesis, the face detection algorithm was accelerated with GPU using OpenCL. The goal was to gain performance benefit while keeping the implementations functionally equivalent. The OpenCL vers

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3

Costa, Rui Jorge Duarte. "Face detection and recognision." Master's thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/21683.

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Mestrado em Engenharia Eletrónica e Telecomunicações<br>Ultimamente, as redes de telecomunicações móveis estão a exigir cada vez maiores taxas de transferência de informação. Com este aumento, embora sejam usados códigos poderosos, também aumenta a largura de banda dos sinais a transmitir, bem como a sua frequência. A maior frequência de operação, bem como a procura por sistemas mais eficientes, tem exigido progressos no que toca aos transístores utilizados nos amplificadores de potência de radio frequência (RF), uma vez que estes são componentes dominantes no rendimento de uma estação base d

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4

Pavani, Sri-Kaushik. "Methods for face detection and adaptive face recognition." Doctoral thesis, Universitat Pompeu Fabra, 2010. http://hdl.handle.net/10803/7567.

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The focus of this thesis is on facial biometrics; specifically in the problems of face detection and face recognition. Despite intensive research over the last 20 years, the technology is not foolproof, which is why we do not see use of face recognition systems in critical sectors such as banking. In this thesis, we focus on three sub-problems in these two areas of research. Firstly, we propose methods to improve the speed-accuracy trade-off of the state-of-the-art face detector. Secondly, we consider a problem that is often ignored in the literature: to decrease the training time of the detec

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5

Day, Adam C. "Designing a face detection CAPTCHA." Morgantown, W. Va. : [West Virginia University Libraries], 2010. http://hdl.handle.net/10450/11036.

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Thesis (M.S.)--West Virginia University, 2010.<br>Title from document title page. Document formatted into pages; contains viii, 80 p. : ill. Includes abstract. Includes bibliographical references (p. 78-80).

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6

Lang, Andreas. "Face Detection using Swarm Intelligence." Universitätsbibliothek Chemnitz, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-64415.

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Groups of starlings can form impressive shapes as they travel northward together in the springtime. This is among a group of natural phenomena based on swarm behaviour. The research field of artificial intelligence in computer science, particularly the areas of robotics and image processing, has in recent decades given increasing attention to the underlying structures. The behaviour of these intelligent swarms has opened new approaches for face detection as well. G. Beni and J. Wang coined the term “swarm intelligence” to describe this type of group behaviour. In this context, intelligence des

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7

McCarroll, Niall. "BioFace : bio-inspired face detection." Thesis, Ulster University, 2017. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.722684.

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The goal of face detection is to determine whether or not an image or video frame contains faces and, if present, return the number of instances of each face object and their location within an image space. Face detection is an important computer vision task as it is the building block for more sophisticated face processing algorithms such as face recognition and facial expression tracking. However, robust and reliable face detection in completely unconstrained settings remains a very challenging task. For example, while the human brain performs face detection and recognition robustly and with

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8

Mahmood, Muhammad Tariq. "Face Detection by Image Discriminating." Thesis, Blekinge Tekniska Högskola, Avdelningen för för interaktion och systemdesign, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4352.

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Human face recognition systems have gained a considerable attention during last few years. There are very many applications with respect to security, sensitivity and secrecy. Face detection is the most important and first step of recognition system. Human face is non rigid and has very many variations regarding image conditions, size, resolution, poses and rotation. Its accurate and robust detection has been a challenge for the researcher. A number of methods and techniques are proposed but due to a huge number of variations no one technique is much successful for all kinds of faces and images

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9

Lang, Andreas. "Face Detection using Swarm Intelligence." Technische Universität Chemnitz, 2010. https://monarch.qucosa.de/id/qucosa%3A19439.

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Groups of starlings can form impressive shapes as they travel northward together in the springtime. This is among a group of natural phenomena based on swarm behaviour. The research field of artificial intelligence in computer science, particularly the areas of robotics and image processing, has in recent decades given increasing attention to the underlying structures. The behaviour of these intelligent swarms has opened new approaches for face detection as well. G. Beni and J. Wang coined the term “swarm intelligence” to describe this type of group behaviour. In this context, intelligence des

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10

Husain, Benafsh Nadir. "Face Detection And Lip Localization." DigitalCommons@CalPoly, 2011. https://digitalcommons.calpoly.edu/theses/601.

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Integration of audio and video signals for automatic speech recognition has become an important field of study. The Audio-Visual Speech Recognition (AVSR) system is known to have accuracy higher than audio-only or visual-only system. The research focused on the visual front end and has been centered around lip segmentation. Experiments performed for lip feature extraction were mainly done in constrained environment with controlled background noise. In this thesis we focus our attention to a database collected in the environment of a moving car which hampered the quality of the imagery. We firs

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11

Westerlund, Tomas. "Fast Face Finding." Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2068.

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<p>Face detection is a classical application of object detection. There are many practical applications in which face detection is the first step; face recognition, video surveillance, image database management, video coding. </p><p>This report presents the results of an implementation of the AdaBoost algorithm to train a Strong Classifier to be used for face detection. The AdaBoost algorithm is fast and shows a low false detection rate, two characteristics which are important for face detection algorithms. </p><p>The application is an implementation of the AdaBoost algorithm with several comm

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12

Wall, Helene. "Context-Based Algorithm for Face Detection." Thesis, Linköping University, Department of Science and Technology, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-4171.

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<p>Face detection has been a research area for more than ten years. It is a complex problem due to the high variability in faces and amongst faces; therefore it is not possible to extract a general pattern to be used for detection. This is what makes the face detection problem a challenge.</p><p>This thesis gives the reader a background to the face detection problem, where the two main approaches of the problem are described. A face detection algorithm is implemented using a context-based method in combination with an evolving neural network. The algorithm consists of two majors steps: detect

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13

Onder, Murat. "Face Detection And Active Robot Vision." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12605290/index.pdf.

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The main task in this thesis is to design a robot vision system with face detection and tracking capability. Hence there are two main works in the thesis: Firstly, the detection of the face on an image that is taken from the camera on the robot must be achieved. Hence this is a serious real time image processing task and time constraints are very important because of this reason. A processing rate of 1 frame/second is tried to be achieved and hence a fast face detection algorithm had to be used. The Eigenface method and the Subspace LDA (Linear Discriminant Analysis) method are implemented, te

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14

Gu, Xiaohan, and Ling Yang. "Face detection based on skin color." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-13767.

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This work is on a method for face detection through analysis of photos. Accurate location of faces and point out the faces are implemented. In the first step, we use Cb and Cr channel to find where the skin color parts are on the photo, then remove noise which around the skin parts, finally, use morphology technique to detect face part exactly. Our result shows this approach can detect faces and establish a good technical based for future face recognition.

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15

Kadoury, Samuel. "Face detection using locally linear embedding." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=98976.

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Human face detection in gray scale images has been researched extensively over the past decade, due to the recent emergence of applications such as security access control, visual surveillance and content-based information retrieval. However, this problem remains challenging because faces are non-rigid objects that have a high degree of variability in size, shape, color and texture. Indeed, few of the proposed face detection methods have been analyzed for performance under different conditions, such as head rotation, illumination, facial expression, occlusion and aging.<br>Nowadays, most face

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16

Bileschi, Stanley Michael 1978. "Advances in component-based face detection." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/87340.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.<br>Includes bibliographical references (leaves 51-53).<br>by Stanley Michael Bileschi.<br>S.M.

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17

Yow, Kin Choong. "Automatic human face detection and localization." Thesis, University of Cambridge, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.624774.

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18

Clemens, Alexander. "Investigating the Inclusivity of Face Detection." Scholarship @ Claremont, 2018. http://scholarship.claremont.edu/cmc_theses/1836.

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Face detection refers to a number of techniques that identify faces in images and videos. As part of the senior project exercise at Pomona College, I explore the process of face detection using a JavaScript library called CLMtrackr. CLMtrackr works in any browser and detects faces within the video stream captured by a webcam. The focus of this paper is to explore the shortcomings in the inclusivity of the CLMtrackr library and consequently that of face detection. In my research, I have used two datasets that contain human faces with diverse backgrounds, in order to assess the accuracy of CLMtr

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Ribeiro, Ricardo Ferreira. "Face detection on infrared thermal image." Master's thesis, Universidade de Aveiro, 2017. http://hdl.handle.net/10773/23551.

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Mestrado em Engenharia Eletrónica e Telecomunicações<br>Infrared cameras or thermal imaging cameras are devices that use infrared radiation to capture an image. This kind of sensors are being developed for almost a century now. They started to be used in the military environment, but at that time it took too long to create a single image. Nowadays, the infrared sensors have reached a whole new technological level and are used for other than military purposes. These sensors are being used for face detection in this thesis. When comparing the use of thermal images regarding color images,

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20

Pongakkasira, Kaewmart. "Face detection in complex natural scenes." Thesis, University of Kent, 2015. https://kar.kent.ac.uk/54792/.

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Face detection is an important preliminary process for all other tasks with faces, such as expression analysis and person identification. It is also known to be rapid and automatic, which indicates that detection might utilise low-level visual information. It has been suggested that this consist of a ‘skin-coloured, face-shaped template’, while internal facial features, such as the eyes, nose and mouth might also help to optimise performance. To explore these ideas directly, this thesis first examined how shape and features are integrated into a detection template (Chapter 2). For this purpose

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21

Liu, Yihui. "Face recognition and face detection based on wavelets and neural networks." Thesis, University of Nottingham, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.403511.

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22

Boulkenafet, Z. (Zinelabidine). "Face presentation attack detection using texture analysis." Doctoral thesis, Oulun yliopisto, 2018. http://urn.fi/urn:isbn:9789526219257.

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Abstract In the last decades, face recognition systems have evolved a lot in terms of performance. As a result, this technology is now considered as mature and is applied in many real world applications from border control to financial transactions and computer security. Yet, many studies show that these systems suffer from vulnerabilities to spoofing attacks, a weakness that may limit their usage in many cases. A face spoofing attack or presentation attack occurs when someone tries to masquerade as someone else by presenting a fake face in front of the face recognition camera. To protect the

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23

Day, Matthew. "Towards optimised cascade classifiers for face detection." Thesis, University of York, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.495869.

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24

Omar, Luma Qassam Abedalqader. "Face liveness detection under processed image attacks." Thesis, Durham University, 2018. http://etheses.dur.ac.uk/12812/.

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Face recognition is a mature and reliable technology for identifying people. Due to high-definition cameras and supporting devices, it is considered the fastest and the least intrusive biometric recognition modality. Nevertheless, effective spoofing attempts on face recognition systems were found to be possible. As a result, various anti-spoofing algorithms were developed to counteract these attacks. They are commonly referred in the literature a liveness detection tests. In this research we highlight the effectiveness of some simple, direct spoofing attacks, and test one of the current robust

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25

Zhou, Yun. "Embedded Face Detection and Facial Expression Recognition." Digital WPI, 2014. https://digitalcommons.wpi.edu/etd-theses/583.

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Face Detection has been applied in many fields such as surveillance, human machine interaction, entertainment and health care. Two main reasons for extensive attention on this typical research domain are: 1) a strong need for the face recognition system is obvious due to the widespread use of security, 2) face recognition is more user friendly and faster since it almost requests the users to do nothing. The system is based on ARM Cortex-A8 development board, including transplantation of Linux operating system, the development of drivers, detecting face by using face class Haar feature and Viol

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26

Norris, Jeffrey S. (Jeffrey Singley) 1976. "Face detection and recognition in office environments." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80108.

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Fraga, António Fernando Crisóstomo. "Parallel Face Detection." Master's thesis, 2020. http://hdl.handle.net/10316/94026.

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Dissertação de Mestrado Integrado em Engenharia Electrotécnica e de Computadores apresentada à Faculdade de Ciências e Tecnologia<br>O reconhecimento de faces em imagens é atualmente feito em grande escala e as imagens utilizadas tende a ser cada vez mais de resolução mais elevadas. Isto pode ser um desafio complicado em arquiteturas sequenciais, pois, com o aumento do número total de pixels das imagens, o desempenho geral desse tipo de implementações tende a diminuir drasticamente. A tese apresentada descreve a implementação de uma framework baseada no artigo Viola-Jones “Rapid Object Detecti

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Sahu, Sameer, and Pappu Thakur. "Human Face Detection." Thesis, 2012. http://ethesis.nitrkl.ac.in/3730/1/Human_face_detection.pdf.

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Face Detection is fast becoming a familiar feature in various technical fields such as video surveillance, military applications, apps and on web, potentially making life easier for us. In current era of social networking Face Detection is a hot topic of research in both academics and commercial area throughout the world. Quite interestingly, the variation in the human skin colour between different races existing in this world primarily is the intensity that is proportional to the amount of melanin in the skin. So our approach towards face detection which uses skin colour seems effective since

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Tsai, Tung-Sheng, and 蔡東昇. "Implementation of Face Detection and Face Tracking." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/91569976255420901425.

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碩士<br>大葉大學<br>資訊工程學系碩士班<br>100<br>In the thesis, we implemented a face detection and tracking system. The developed system is composed of two main parts: face detection and face tracking. In the face detection part, a face detector using Haar-Like features trained by Adaboost algorithm is adopted to detect facial region. To remove the error of face region, the human eyes information can also be used. After the face detection was completed, each face candidate can be tracked in the temporal domain. In the face tracking part, KLT features are extracted and tracked between two adjacent frames. Ba

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chao, chang min, and 張閔詔. "Covered Face Detection and RecognitionCovered Face Detection and Recognition using Decision Tree." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/05130351792301190914.

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謝昌甫. "Human face detection system." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/33813411288787563185.

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碩士<br>中華大學<br>資訊工程學系碩士班<br>89<br>With the improvement of science and technology, the usage of human-machine interface is more popular and convenient in the recent years. A fast and accu-rate face detection approach is important for several applications, such as face recognition, security system, human-machine interface and TV-conference,etc. This thesis proposes a new method to detect human eyes and uses feature-based approach with fuzzy logic theorem for face candidates confirmation. According to this detecting scheme, we can obtain the face location, face tilt angle, face size and

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Ferreira, José Duarte Penetro Mesquita. "Cross-Sensor Face Detection." Master's thesis, 2021. https://hdl.handle.net/10216/135359.

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Ferreira, José Duarte Penetro Mesquita. "Cross-Sensor Face Detection." Dissertação, 2021. https://hdl.handle.net/10216/135359.

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Tuyen, Kha Kim, and 柯金泉. "Face Detection with RetinaNet." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/y7r4c6.

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碩士<br>國立中央大學<br>資訊工程學系在職專班<br>107<br>Abstract Face detection is a critical step for many face-related applications, such as face alignment, face verification, face identification, crowed behavior analysis etc. However, small size, occlusion, illumination, pose deformation, expression and other disadvantageous factors often appear in real-world images, which bring great challenges to face detection. Besides, computation cost is also a big challenge for face detection in real-time application. Traditional approach use manual operation with slide windows to skim and detect face location, it cos

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李宗岳. "Dynamic Face Detection via Adaptive Face Features Extraction." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/07139451006948106318.

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36

Ren-Shan, Luoh, and 駱仁山. "A Study of Face Detection for Face Recognition." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/55999885264256830205.

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碩士<br>國立交通大學<br>資訊工程系<br>87<br>We propose a method for detecting human faces in a color picture. By applying a skin color model, we label some rectangular regions in the picture as skin. After merging several small skin regions and sifting the proper ones, we can quickly locate the possible face images in a picture. Since the skin regions are relative smaller than the original picture image, the overall computing time can be greatly reduced. In order to precisely locate the eye in the face image, we use so

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Chen, Chihhao, and 陳致豪. "Speedup AdaBoost Face Detection by Skin Color Detection." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/44807696820261382608.

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碩士<br>明志科技大學<br>電子工程研究所<br>99<br>Study on human face detection is originated from human face recognition, and it aims to recognize human face in images and identify the position of human face. In modern time, with the prevalence of imaging system and the rise of computer vision, researches on human face detection develop rapidly. This study proposes a human face detection method based on dynamic images. The paper is organized into four parts. 1) It first implements the human face detection proposed by Viola upon AdaBoost, and analyze efficacy by cascade provided by OpenCV. 2) It then develops

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Hu, Shyuegong, and 胡學恭. "Multiple-Face Detection & Face Recognition for Complex Backgrounds." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/87643401522123211970.

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碩士<br>元智大學<br>資訊管理學系<br>98<br>Human face detection and human face recognition are always popular topics in pattern recognition, they have develop for a long time, and its technique has become more and more robust. At the past, some technique could be restricted by hardware or other experimental settings, so they should made some kind of trade off between detection rate, recognition rate and computing time. Now days, with the development of technology and other equipment some time consuming methods become available. We present a human face detection method which is base on haar-like features a

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Serre, Thomas, Bernd Heisele, Sayan Mukherjee, and Tomaso Poggio. "Feature Selection for Face Detection." 2000. http://hdl.handle.net/1721.1/7232.

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We present a new method to select features for a face detection system using Support Vector Machines (SVMs). In the first step we reduce the dimensionality of the input space by projecting the data into a subset of eigenvectors. The dimension of the subset is determined by a classification criterion based on minimizing a bound on the expected error probability of an SVM. In the second step we select features from the SVM feature space by removing those that have low contributions to the decision function of the SVM.

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Mei-Heng, Lin, and 林美亨. "Face Detection in Scalable Video." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/03355681428582322876.

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碩士<br>國立交通大學<br>資訊學院碩士在職專班資訊組<br>95<br>3D wavelet scalable video coding has the advantages of bandwith, temporal, and spatial scalability, which includes three main modules : T_Module、S_Module、Entropy_Coding, those produce final compressed output bit stream. In this thesis we would like to combine face detection in 3D wavelet scalable video. The advantages are: 1. User only download one bit stream and extract it for what they need. 2. Server only provides one bit stream for all users to download and it also saves lots of disk space in network. We propose a strategy that makes the face can b

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Effendi, Mohammad Khoirul, and 仁迪芬. "Cascade AdaBoost for Face Detection." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/15976892970662808799.

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碩士<br>國立臺灣科技大學<br>機械工程系<br>98<br>AdaBoost is a well developed method for classification, and has been applied to face detection. Given a large set of training data, AdaBoost-based face detector combines many weak classifiers, each of which is targeted at a set of features with different characteristics, and generates a strong classifier able to detect faces with large variations on the appearances. However, when the patterns embedded in the positive and negative training data conflict to each other, the training can often become time-consuming, and in some cases, be extremely difficult to conv

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李俊達. "Face detection in Color Image." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/06137633306875184263.

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碩士<br>國立政治大學<br>資訊科學學系<br>95<br>The main goal of this thesis is to detect human face under varying lighting condition by utilizing multiple color space information in real-time. Images of RGB color space can be converted into normalized RGB and HSV color spaces and thus reduce the interference of lighting condition. Base on this mechanism, we define 8 Haar-like features inside 4 selected color spaces, and then select the important features with boosting algorithm. Experimental results show that detectors constructed with our approach are able to process nearly one million sub-windows within 2.

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Jhang, Yuan-Ruei, and 張元睿. "Face Detection in Still Image." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/78355345614201711713.

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碩士<br>國立臺灣大學<br>醫學工程學研究所<br>92<br>Within the automatic human face identification system, a good human face detecting system is needed to serve as a prerequisite, yet within a standstill grey scale image, there is only an intensity variation value on each image element, which lacks information on colored and sequential image, therefore, to be able to accurately circle out the size of the human face within the image and its position only increases its difficulty. Currently majority of the literary review only utilized image’s grey scale value on the mechanical learning or statistic analysis to

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Shen, Chi-Liang, and 沈啟亮. "Real Time Face Detection System." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/51621379084753012144.

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碩士<br>淡江大學<br>電機工程學系碩士在職專班<br>92<br>Real-time face detection and face recognition from cluttered images is a challenging work. This dissertation proposes a hierarchical window based on the facial features as an operating mask for human eyes detection so as to be adaptable for different face sizes in images. After the input image is processed using the Sobel filter edge detection, we first make use of the characteristics of symmetric relationships of human-eyes region to find out the possible region of human eyes. Then, to exclude the region of without-human eyes and quickly reach the locations

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Sun, Shih-Ching, and 孫世清. "Real Time Face Detection Algorithm." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/24896181450898652075.

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碩士<br>國立東華大學<br>電機工程學系<br>91<br>In recent years, human face detection is becoming more and more popular. Automatically detecting human faces is becoming a very important task in various applications such as video surveillance, human computer interface, face recognition and face image database management. In the face recognition application, the human face location must be known before the processing. The face tracking application also needs a predefined face location at first. In the face image database management, the human faces must be discovered as fast as possible due to the large image d

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Chou, Heng-Shen, and 周恆生. "Face Detection in Color Images." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/88891165686958406869.

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碩士<br>國立清華大學<br>資訊工程學系<br>91<br>Due to the rapid growth of technologies for network and multimedia, digital input devices have become more and more popular, and the cost of the digital image is much lower now. Various applications which using facial features like personal identify and facial expression capture are coming to the mature period. However, face detection plays an important role in these issues. A good face detection algorithm could slash the computational time in verifying probable face candidates, and improve the comparing efficiency. In this paper, we propose a face de

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Lee, Tsung-Pei, and 李宗霈. "Face Detection on Embedded Systems." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/99454969346388372578.

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碩士<br>國立臺北教育大學<br>資訊科學系碩士班<br>103<br>Vehicle inventions facilitate human life but also pose a threat to human lives. The slightest mistake while operating them frequently caused heavy casualties and loss of life. Thus, traffic safety issues have the wide attention of governments. Biometrics can automatically identify the individual physiological or behavioral aspect of the system. Different conditions can be set according to different needs in order to achieve the desired purpose. Face detection is the basis for automation systems. Face application needs to have strong face detection methods i

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Garcia, Jorge Renato Torres. "Face detection from video streaming." Master's thesis, 2018. https://hdl.handle.net/10216/112424.

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Chang, Yen-An, and 張宴安. "Human Face Detection and Application." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/32868867088619962367.

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碩士<br>淡江大學<br>電機工程學系碩士班<br>95<br>Recently, the Biosensor system has been mostly applied to the security of the community or the company. Despite the efficiency of the identification of the human’s figure, this system isn’t applied extensively in our society. The aim of this thesis is to propose a sound human-face detection and recognition system that is different from the traditional one, which can only tell whether the figure passes the detection or not without taking any further measurement. The system proposed here can find out whether the figure is masked or not and then proceed to recogni

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Kuo, Tsung-Yu, and 郭宗祐. "Face Detection Using Geometrical Information." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/58216973606685499337.

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碩士<br>義守大學<br>資訊工程學系碩士班<br>94<br>This thesis aims to the study of face detection system. First, histogram of image intensity is computed from an image. According to the peak value of the histogram, we can determine a threshold and then find the pixels that could be eye candidates. These pixels are merged to eye candidates that are represented by a binary image. To identify which one is a real eye, we examine each of its area and remove the impossible ones. Finally, we compute the convolution integral of each candidate and a simple mask that is designed based on geometrical information of human

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