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Técnicas de seleção de características com aplicações em reconhecimento de faces.; Feature selection techniques with applications to face recognition.

Campos, Teófilo Emídio de
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 25/05/2001 PT
Relevância na Pesquisa
66.28%
O reconhecimento de faces é uma área de pesquisa desafiadora que abre portas para a implementação de aplicações muito promissoras. Embora muitos algoritmos eficientes e robustos já tenham sido propostos, ainda restam vários desafios. Dentre os principais obstáculos a serem uperados, está a obtenção de uma representação robusta e compacta de faces que possibilite distinguir os indivíduos rapidamente. Visando abordar esse problema, foi realizado um estudo de técnicas de reconhecimento estatístico de padrões, principalmente na área de redução de dimensionalidade dos dados, além de uma revisão de métodos de reconhecimento de faces. Foi proposto (em colaboração com a pesquisadora Isabelle Bloch) um método de seleção de características que une um algoritmo de busca eficiente (métodos de busca seqüencial flutuante) com uma medida de distância entre conjuntos nebulosos (distância nebulosa baseada em tolerância). Essa medida de distância possui diversas vantagens, sendo possível considerar as diferentes tipicalidades de cada padrão dos conjuntos de modo a permitir a obtenção de bons resultados mesmo com conjuntos com sobreposição. Os resultados preliminares com dados sintéticos mostraram o caráter promissor dessa abordagem. Com o objetivo de verificar a eficiência de tal técnica com dados reais...

Reconhecimento de faces humanas usando redes neurais MLP; Human face recognition using MLP neural networks

Gaspar, Thiago Lombardi
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 15/02/2006 PT
Relevância na Pesquisa
66.27%
O objetivo deste trabalho foi desenvolver um algoritmo baseado em redes neurais para o reconhecimento facial. O algoritmo contém dois módulos principais, um módulo para a extração de características e um módulo para o reconhecimento facial, sendo aplicado sobre imagens digitais nas quais a face foi previamente detectada. O método utilizado para a extração de características baseia-se na aplicação de assinaturas horizontais e verticais para localizar os componentes faciais (olhos e nariz) e definir a posição desses componentes. Como entrada foram utilizadas imagens faciais de três bancos distintos: PICS, ESSEX e AT&T. Para esse módulo, a média de acerto foi de 86.6%, para os três bancos de dados. No módulo de reconhecimento foi utilizada a arquitetura perceptron multicamadas (MLP), e para o treinamento dessa rede foi utilizado o algoritmo de aprendizagem backpropagation. As características faciais extraídas foram aplicadas nas entradas dessa rede neural, que realizou o reconhecimento da face. A rede conseguiu reconhecer 97% das imagens que foram identificadas como pertencendo ao banco de dados utilizado. Apesar dos resultados satisfatórios obtidos, constatou-se que essa rede não consegue separar adequadamente características faciais com valores muito próximos...

Caricatura e reconhecimento de faces; Caricature and face recognition

Mendes, Ana Irene Fonseca
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 29/01/2008 PT
Relevância na Pesquisa
66.34%
A caricatura, uma imagem da face baseada no exagero de suas características peculiares, geralmente é reconhecida tão bem quanto a fotografia da face sem distorções. Para confecção das caricaturas, exageram-se as diferenças entre a imagem original e um protótipo (face média de um grupo de pessoas); e para confecção das anti-caricaturas essas diferenças são atenuadas. O objetivo desta pesquisa foi investigar se existe um grau de exagero ótimo para que a caricatura represente a face melhor que a fotografia original. Além disso, investigou- se o papel da percepção holística versus percepção componencial no processo de reconhecimento de faces. Foram geradas seis faces prototípicas, masculinas e femininas, de pessoas da população da região de Ribeirão Preto que se auto-declaram branca, parda e preta. A partir das faces prototípicas, foram gerados dois tipos de caricaturas e anticaricaturas: 1. holística: em que todas as diferenças entre a face original e a prototípica foram manipuladas, 2. parcial: em que somente as diferenças de alguns elementos faciais isolados ou combinados entre a face original e a prototípica foram manipuladas. No Experimento I os estímulos teste foram as caricaturas e anti-caricaturas holísticas. No Experimento II os estímulos foram as caricaturas e anti-caricaturas parciais. Em ambos experimentos as caricaturas e anti-caricaturas foram submetidas a julgamentos de similaridade com a face original previamente memorizada. Os resultados do Experimento I indicaram que a melhor representação da face é a fotografia sem distorção e que...

Improving face recognition with multispectral fusion and support vector machines

Chiachia, Giovani
Fonte: Universidade Estadual Paulista (UNESP) Publicador: Universidade Estadual Paulista (UNESP)
Tipo: Dissertação de Mestrado Formato: 86 f. : il. color.
ENG
Relevância na Pesquisa
66.39%
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES); Pós-graduação em Ciência da Computação - IBILCE; O reconhecimento facial é uma das principais formas de identificação humana. Apesar das pesquisas em reconhecimento facial automático terem crescido substancialmente ao longo dos últimos 35 anos, identificar pessoas a partir da face continua sendo um desafio para as áreas de Visão Computacional e Reconhecimento de Padrões. Em função dos cenários variarem desde a identificação a partir de fotografias até o reconhecimento baseado em vídeos sem nenhum tipo de controle ao serem gravados, os maiores desafios estão relacionados à independência contra diferentes tipos de iluminação, pose e expressão. O objetivo desta dissertação é propor técnicas que possam contribuir para a melhoria dos sistemas de reconhecimento facial. A primeira técnica endereça o problema da iluminação através da fusão dos espectros visível e infravermelho da face. Através desta abordagem, as taxas de reconhecimento foram melhoradas em 2.07% enquanto a taxa de erro igual (EER) foi reduzida em 45.47%. A segunda técnica trata do caso da extração e classificação de características faciais. Ela propõe um novo modelo para reconhecimento facial através do uso de características extraídas por Histogramas Census e de uma técnica de reconhecimento de padrões baseada em Máquinas de Vetores de Suporte (SVMs). Este outro grupo de experimentos nos possibilitou aumentar a precisão do reconhecimento no teste FERET fa/fb em 0.5%. Além destes resultados...

A maximum uncertainty LDA-based approach for limited sample size problems - with application to face recognition

Thomaz,Carlos Eduardo; Kitani,Edson Caoru; Gillies,Duncan Fyfe
Fonte: Sociedade Brasileira de Computação Publicador: Sociedade Brasileira de Computação
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/09/2006 EN
Relevância na Pesquisa
66.25%
A critical issue of applying Linear Discriminant Analysis (LDA) is both the singularity and instability of the within-class scatter matrix. In practice, particularly in image recognition applications such as face recognition, there are often a large number of pixels or pre-processed features available, but the total number of training patterns is limited and commonly less than the dimension of the feature space. In this study, a new LDA-based method is proposed. It is based on a straightforward stabilisation approach for the within-class scatter matrix. In order to evaluate its effectiveness, experiments on face recognition using the well-known ORL and FERET face databases were carried out and compared with other LDA-based methods. The classification results indicate that our method improves the LDA classification performance when the within-class scatter matrix is not only singular but also poorly estimated, with or without a Principal Component Analysis intermediate step and using less linear discriminant features. Since statistical discrimination methods are suitable not only for classification but also for characterisation of differences between groups of patterns, further experiments were carried out in order to extend the new LDA-based method to visually analyse the most discriminating hyper-plane separating two populations. The additional results based on frontal face images indicate that the new LDA-based mapping provides an intuitive interpretation of the two-group classification tasks performed...

Proposing the novelty classifier for face recognition

Costa Filho,Cicero Ferreira Fernandes; Falcão,Thiago de Azevedo; Costa,Marly Guimarães Fernandes; Pereira,José Raimundo Gomes
Fonte: SBEB - Sociedade Brasileira de Engenharia Biomédica Publicador: SBEB - Sociedade Brasileira de Engenharia Biomédica
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/12/2014 EN
Relevância na Pesquisa
66.31%
INTRODUCTION: Face recognition, one of the most explored themes in biometry, is used in a wide range of applications: access control, forensic detection, surveillance and monitoring systems, and robotic and human machine interactions. In this paper, a new classifier is proposed for face recognition: the novelty classifier. METHODS: The performance of a novelty classifier is compared with the performance of the nearest neighbor classifier. The ORL face image database was used. Three methods were employed for characteristic extraction: principal component analysis, bi-dimensional principal component analysis with dimension reduction in one dimension and bi-dimensional principal component analysis with dimension reduction in two directions. RESULTS: In identification mode, the best recognition rate with the leave-one-out strategy is equal to 100%. In the verification mode, the best recognition rate was also 100%. For the half-half strategy, the best recognition rate in the identification mode is equal to 98.5%, and in the verification mode, 88%. CONCLUSION: For face recognition, the novelty classifier performs comparable to the best results already published in the literature, which further confirms the novelty classifier as an important pattern recognition method in biometry.

Development of Face Recognition: Infancy to Early Childhood

Argumosa, Melissa Ann
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica Formato: application/pdf
Relevância na Pesquisa
66.39%
Perception and recognition of faces are fundamental cognitive abilities that form a basis for our social interactions. Research has investigated face perception using a variety of methodologies across the lifespan. Habituation, novelty preference, and visual paired comparison paradigms are typically used to investigate face perception in young infants. Storybook recognition tasks and eyewitness lineup paradigms are generally used to investigate face perception in young children. These methodologies have introduced systematic differences including the use of linguistic information for children but not infants, greater memory load for children than infants, and longer exposure times to faces for infants than for older children, making comparisons across age difficult. Thus, research investigating infant and child perception of faces using common methods, measures, and stimuli is needed to better understand how face perception develops. According to predictions of the Intersensory Redundancy Hypothesis (IRH; Bahrick & Lickliter, 2000, 2002), in early development, perception of faces is enhanced in unimodal visual (i.e., silent dynamic face) rather than bimodal audiovisual (i.e., dynamic face with synchronous speech) stimulation. The current study investigated the development of face recognition across children of three ages: 5 – 6 months...

Subspace-based face recognition: Outlier detection and a new distance criterion

Chen, P.; Suter, D.
Fonte: World Scientific Publ Co Pte Ltd Publicador: World Scientific Publ Co Pte Ltd
Tipo: Artigo de Revista Científica
Publicado em //2005 EN
Relevância na Pesquisa
66.25%
Illumination effects, including shadows and varying lighting, make the problem of face recognition challenging. Experimental and theoretical results show that the face images under different illumination conditions approximately lie in a low-dimensional subspace, hence principal component analysis (PCA) or low-dimensional subspace techniques have been used. Following this spirit, we propose new techniques for the face recognition problem, including an outlier detection strategy (mainly for those points not following the Lambertian reflectance model), and a new error criterion for the recognition algorithm. Experiments using the Yale-B face database show the effectiveness of the new strategies.; Pei Chen and David Suter

A study of the eigenface approach for face recognition

Chin, Tat-Jun; Suter, David
Fonte: Monash University Publicador: Monash University
Tipo: Relatório
Publicado em //2004 EN
Relevância na Pesquisa
66.27%
Appearance-based approaches in face recognition, specifically the Eigenface approach, were one of first successful demonstrations of machine recognition of faces [1]. These methods, such as those proposed in [2, 3], proved to be effective in experiments with large databases. Further development of holistic methods of face recognition and their theoretical background, such as those proposed in [4-9], were focused towards recognizing faces from images with changes caused by illumination effects and pose variations. Although much effort has been made towards this goal, current algorithms are still far away from the capability of the human perception system [1]. This report shall give a detailed description of the fundamentals of appearance-based holistic methods for face recognition, specifically the Eigenface approach [3], as well as our experimental results on the Yale Face Database.

A Practical Case Study: Face Recognition on Low Quality Images Using Gabor Wavelet and Support Vector Machines

Martí, Enrique David; Patricio Guisado, Miguel Ángel; Molina, José M.
Fonte: Springer Publicador: Springer
Tipo: info:eu-repo/semantics/acceptedVersion; info:eu-repo/semantics/article
Publicado em /12/2011 ENG
Relevância na Pesquisa
66.29%
Face recognition is a problem that arises on many real world applications, such as those related with Ambient Intelligence (AmI). The specific nature and goals of AmI applications, however, requires minimizing the invasiveness of data collection methods, often resulting in a drastic reduction of data quality and a plague of unforeseen effects which can put standard face recognition systems out of action. In order to deal with this, a face recognition system for AmI applications must not only be carefully designed but also subject to an exhaustive configuration plan to ensure it offers the required accuracy, robustness and real-time performance. This document covers the design and tuning of a holistic face recognition system targeting an Ambient Intelligence scenario. It has to work under partially uncontrolled capturing conditions: frontal images with pose variation up to 40 degrees, changing illumination, variable image size and degraded quality. The proposed system is based on Support Vector Machine (SVM) classifiers and applies Gabor Filters intensively. A complete sensitivity analysis shows how the recognition accuracy can be boosted through careful configuration and proper parameter setting, although the most adequate setting depends on the requirements for the final system.; This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI...

Comparação entre algoritmos de reconhecimento de face no contexto de acessibilidade; Comparison between face recognition algorithms in acessibility context

Douglas Eduardo Parra
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 27/06/2014 PT
Relevância na Pesquisa
66.31%
Nesta dissertação de mestrado, é mostrada uma comparação entre três algoritmos de reconhecimento de face no contexto de acessibilidade para o projeto Microsoft com parceria com a FAPESP, para o módulo de reconhecimento de pessoas utilizando o Microsoft Kinect e substituição sensorial. O algoritmo k-Nearest Neighbours, junto do descritor Histograma de Gradientes Orientados, foi utilizado como base por ser uma abordagem simples e de baixo custo computacional. Os algoritmos Eigenfaces e Local Binary Pattern Histogram foram comparados com o anterior em quatro experimentos. Inicialmente, é descrito o Projeto Vision for the Blind e seus diversos módulos. Este projeto foi desenvolvido por uma equipe aqui no Brasil, que obteve bons resultados para os módulos de navegação e reconhecimento de face, sempre com a ideia de usar o áudio 3D para passar a informação desejada ao usuário. Em seguida, é apresentada uma revisão do estado da arte com projetos no contexto de acessibilidade e substituição sensorial, apontando suas limitações. Logo após é feita uma revisão sobre os três algoritmos de reconhecimento facial utilizados e, então, como foi construída o banco de imagens deste projeto. Foram obtidos bons resultados com os três algoritmos...

Capturing Specific Abilities as a Window into Human Individuality: The Example of Face Recognition

Wilmer, Jeremy Bennet; Germine, Laura Thi; Chabris, Christopher; Chatterjee, Garga; Gerbasi, Margaret E; Nakayama, Ken
Fonte: Taylor & Francis Publicador: Taylor & Francis
Tipo: Artigo de Revista Científica
EN_US
Relevância na Pesquisa
66.34%
Proper characterization of each individual's unique pattern of strengths and weaknesses requires good measures of diverse abilities. Here, we advocate combining our growing understanding of neural and cognitive mechanisms with modern psychometric methods in a renewed effort to capture human individuality through a consideration of specific abilities. We articulate five criteria for the isolation and measurement of specific abilities, then apply these criteria to face recognition. We cleanly dissociate face recognition from more general visual and verbal recognition. This dissociation stretches across ability as well as disability, suggesting that specific developmental face recognition deficits are a special case of a broader specificity that spans the entire spectrum of human face recognition performance. Item-by-item results from 1,471 web-tested participants, included as supplementary information, fuel item analyses, validation, norming, and item response theory (IRT) analyses of our three tests: (a) the widely used Cambridge Face Memory Test (CFMT); (b) an Abstract Art Memory Test (AAMT), and (c) a Verbal Paired-Associates Memory Test (VPMT). The availability of this data set provides a solid foundation for interpreting future scores on these tests. We argue that the allied fields of experimental psychology...

A Realistic Simulation Tool for Testing Face Recognition Systems under Real-World Conditions

Verschae, Rodrigo; Ruiz del Solar, Javier; Parra-Tsunekawa, Sebastián Isao; Correa, Mauricio
Fonte: Universidade do Chile Publicador: Universidade do Chile
Tipo: Artículo de revista
EN
Relevância na Pesquisa
66.34%
In this article, a tool for testing face recognition systems under uncontrolled conditions is proposed. The key elements of this tool are a simulator and real face and background images taken under real-world conditions with different acquisition angles. Inside the simulated environment, an observing agent, the one with the ability to recognize faces, can navigate and observe the real face images, at different distances, angles and with indoor or outdoor illumination. During the face recognition process, the agent can actively change its viewpoint and relative distance to the faces in order to improve the recognition results. The simulation tool provides all functionalities to the agent (navigation, positioning, face’s image composing under different angles, etc.), except the ones related with the recognition of faces. This tool could be of high interest for HRI applications related with the visual recognition of humans, as the ones included in the RoboCup @Home league. It allows comparing and quantifying the face recognition capabilities of service robots under exactly equal working conditions. It could be a complement to existing tests in the RoboCup @Home league. The applicability of the proposed tool is validated in the comparison of three state of the art face recognition methods.; This research was partially funded by FONDECYT under Project Number 1090250.

A comparative study of thermal face recognition methods in unconstrained environments

Ruiz del Solar, Javier; Verschae, Rodrigo; Correa, Mauricio; Hermosilla, Gabriel
Fonte: Elsevier Publicador: Elsevier
Tipo: Artículo de revista
EN
Relevância na Pesquisa
66.28%
Artículo de publicación ISI; The recognition of faces in unconstrained environments is a challenging problem. The aim of this work is to carry out a comparative study of face recognition methods working in the thermal spectrum (8-12 mu m) that are suitable for working properly in these environments. The analyzed methods were selected by considering their performance in former comparative studies, in addition to being real-time, to requiring just one image per person, and to being fully online (no requirements of offline enrollment). Thus, in this study three local-matching methods based on histograms of Local Binary Pattern (LBP) features, on histograms of Weber Linear Descriptors (WLD), and on Gabor Jet Descriptors (GJD), as well as two global image-matching method based on Scale-Invariant Feature Transform (SIFT) Descriptors, and Speeded Up Robust Features (SURF) Descriptors, are analyzed. The methods are compared using the Equinox and UCHThermalFace databases. The use of these databases allows evaluating the methods in real-world conditions that include natural variations in illumination, indoor/outdoor setup, facial expression, pose, accessories, occlusions, and background. The UCHThermalFace database is described for the first time in this article and WLD is used for the first time in face recognition. The results of this comparative study are intended to be a guide for developers of face recognition systems. The main conclusions of this study are: (i) all analyzed methods perform very well under the conditions in which they were evaluated...

Methodological improvement on local Gabor face recognition based on feature selection and enhanced Borda count

Castillo, Luis E.; Cament, Leonardo A.; Pérez, Claudio A.
Fonte: Elsevier Publicador: Elsevier
Tipo: Artículo de revista
EN
Relevância na Pesquisa
66.36%
Artículo de publicación ISI; Face recognition has a wide range of possible applications in surveillance, human computer interfaces and marketing and advertising goods for selected customers according to age and gender. Because of the high classification rate and reduced computational time, one of the best methods for face recognition is based on Gabor jet feature extraction and Borda count classification. In this paper, we propose methodological improvements to increase face recognition rate by selection of Gabor jets using entropy and genetic algorithms. This selection of jets additionally allows faster processing for real-time face recognition. We also propose improvements in the Borda count classification through a weighted Borda count and a threshold to eliminate low score jets from the voting process to increase the face recognition rate. Combinations of Gabor jet selection and Borda count improvements are also proposed. We compare our results with those published in the literature to date and find significant improvements. Our best results on the FERET database are 99.8%, 99.5%, 89.2% and 86.8% recognition rates on the subsets Fb, Fc, Dup1 and Dup2, respectively. Compared to the best results published in the literature, the total number of recognition errors decreased from 163 to 112 (31%). We also tested the proposed method under illumination changes...

Face Recognition in Unconstrained Environments: A Comparative Study

Ruiz del Solar, Javier; Correa, Mauricio; Verschae, Rodrigo
Fonte: Universidade do Chile Publicador: Universidade do Chile
Tipo: Artículo de revista
EN
Relevância na Pesquisa
66.27%
The development of face recognition methods for unconstrained environments is a challenging problem. The aim of this work is to carry out a comparative study of existing face recognition methods that are suitable to work properly in these environments. The analyzed methods are selected by considering their performance in former comparative studies, in addition to be real-time, to require just one image per person, and to be fully online (no requirements of offline enrollment). The methods are compared using the LFW database, which was built to evaluate face recognition methods in real-world conditions. The results of this comparative study are intended to be a guide for developers of face recognition systems.

Illumination compensation and normalization in eigenspace-based face recognition: A comparative study of different pre-processing approaches

Quinteros, Julio; Ruiz del Solar, Javier
Fonte: ELSEVIER SCIENCE BV Publicador: ELSEVIER SCIENCE BV
Tipo: Artículo de revista
EN
Relevância na Pesquisa
66.3%
The aim of this work is to investigate illumination compensation and normalization in eigenspace-based face recognition by carrying out an independent comparative study among several pre-processing algorithms. This research is motivated by the lack of direct and detailed comparisons of those algorithms in equal working conditions. The results of this comparative study intend to be a guide for the developers of face recognitions systems. The study focuses on algorithms with the following properties: (i) general purpose, (ii) no modeling steps or training images required, (iii) simplicity, (iv) high speed, and (v) high performance in terms of recognition rates. Thus, herein five different algorithms are compared, by using them as a pre-processing stage in 16 different eigenspace-based face recognition systems. The comparative study is carried out in a face identification scenario using a large amount of images from the PIE, Yale B and Notre Dame face databases. As a result of this study we concluded that the most suitable algorithms for achieving illumination compensation and normalization in eigenspace-based face recognition are SQI and the modified LBP transform.

3D Model Based Pose Invariant Face Recognition from a Single Frontal View

Chen, Qinran; Cham, Wai-kuen
Fonte: Universidade Autônoma de Barcelona Publicador: Universidade Autônoma de Barcelona
Tipo: Artigo de Revista Científica Formato: application/pdf
Publicado em //2007 ENG
Relevância na Pesquisa
66.29%
This paper proposes a 3D model based pose invariant face recognition method that can recognize a face of a large rotation angle from its single nearly frontal view. The proposed method achieves the goal by using an analytic-to-holistic approach and a novel algorithm for estimation of ear points. Firstly, the proposed method achieves facial feature detection, in which an edge map based algorithm is developed to detect the ear points. Based on the detected facial feature points 3D face models are computed and used to achieve pose estimation. Then we reconstruct the facial feature points’ locations and synthesize facial feature templates in frontal view using computed face models and estimated poses. Finally, the proposed method achieves face recognition by corresponding template matching and corresponding geometric feature matching. Experimental results show that the proposed face recognition method is robust for pose variations including both seesaw rotations and sidespin rotations.

Face recognition with variation in pose angle using face graphs

Kumar, Sooraj
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
EN_US
Relevância na Pesquisa
66.39%
Automatic recognition of human faces is an important and growing field. Several real-world applications have started to rely on the accuracy of computer-based face recognition systems for their own performance in terms of efficiency, safety and reliability. Many algorithms have already been established in terms of frontal face recognition, where the person to be recognized is looking directly at the camera. More recently, methods for non-frontal face recognition have been proposed. These include work related to 3D rigid face models, component-based 3D morphable models, eigenfaces and elastic bunched graph matching (EBGM). This thesis extends recognition algorithm based on EBGM to establish better face recognition across pose variation. Facial features are localized using active shape models and face recognition is based on elastic bunch graph matching. Recognition is performed by comparing feature descriptors based on Gabor wavelets for various orientations and scales, called jets. Two novel recognition schemes, feature weighting and jet-mapping, are proposed for improved performance of the base scheme, and a combination of the two schemes is considered as a further enhancement. The improvements in performance have been evaluated by studying recognition rates on an existing database and comparing the results with the base recognition scheme over which the schemes have been developed. Improvement of up to 20% has been observed for face pose variation as large as 45°.

Face recognition in low resolution video sequences using super resolution

Arachchige, Somi Ruwan Budhagoda
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Tese de Doutorado
EN_US
Relevância na Pesquisa
66.36%
Human activity is a major concern in a wide variety of applications, such as video surveillance, human computer interface and face image database management. Detecting and recognizing faces is a crucial step in these applications. Furthermore, major advancements and initiatives in security applications in the past years have propelled face recognition technology into the spotlight. The performance of existing face recognition systems declines significantly if the resolution of the face image falls below a certain level. This is especially critical in surveillance imagery where often, due to many reasons, only low-resolution video of faces is available. If these low-resolution images are passed to a face recognition system, the performance is usually unacceptable. Hence, resolution plays a key role in face recognition systems. In this thesis, we address this issue by using super-resolution techniques as a middle step, where multiple low resolution face image frames are used to obtain a high-resolution face image for improved recognition rates. Two different techniques based on frequency and spatial domains were utilized in super resolution image enhancement. In this thesis, we apply super resolution to both images and video utilizing these techniques and we employ principal component analysis for face matching...