The master thesis deals with the topic of detecting faces in digital images. There are generally described and classified the most frequently used methods and discussed their advantages and disadvantages. More detailed is described skin color detection, eye and mouth detection and are teoretically described machine learning algorithms and detection based on Haar-classifiers. The work aims to implementation of these methods in the OpenCV library, it refers to practical application of them a finally compares different provided trained files.

The presented master thesis deals with the evaluation of the position of the iris compared with surroundings of the eye. This technique is supposed to be use for computer control. The created software works in real-time mode, the pictures are taken with an ordinary webcam. The first part of the work presents basic algorithms used in computer vision for edit of images. The following part is focused on abilities of methods to find the face, eyes and to detect the iris. The detection and the subsequent separation of the face is based on the recognition of skin colour in the YCbCr color space. The position of eye is then searched in the face by Haar-like features. The darkest part of the eye is found by horizontal projection from surroundings and the seed point is started from this place. From the area which is filled by the seed method (Flood Fill) and which shows the iris, the cursor movement is controlled by obtained x and y position.

Les humains sont capables de suivre visuellement des objets sans effort. Cependant les algorithmes de vision artificielle rencontrent des limitations pour suivre des objets en mouvement rapide, sous un éclairage variable, en présence d'occultations, dans un environnement complexe ou dont l'apparence varie à cause de déformations et de changements de point de vue. Parce que des systèmes génériques, précis, robustes et rapides sont nécessaires pour de nombreuses d’applications, le suivi d’objets reste un problème pratique important en vision par ordinateur. La première contribution de cette thèse est une approche calculatoire rapide pour le suivi d'objets de forme et de mouvement variable. Elle consiste en un système unifié et configurable pour estimer l'attitude d’un objet déformable dans un espace d'états de dimension petite ou grande. L’objet est décomposé en une suite de segments composés de parties et organisés selon une hiérarchie spatio-temporelle contrainte. L'efficacité et l’universalité de cette approche sont démontrées expérimentalement sur de nombreux exemples de suivi de divers objets flexibles et articulés. Les caractéristiques de Haar (HLF) sont abondement utilisées pour le suivi d’objets. La deuxième contribution est une méthode de décomposition des HLF permettant de les calculer de manière efficace. Ces caractéristiques sont décomposées en noyaux plus simples, éventuellement réutilisables, et reformulées comme des convolutions multi-passes. La recherche et l'alignement des noyaux dans et entre les passes permet de créer des arbres récursifs de noyaux qui nécessitent moins d’opérations en mémoire que les systèmes de calcul classiques, pour un résultat de convolution identique et une mise en œuvre plus efficace. Cette approche a été validée expérimentalement sur des exemples de HLF très utilisés / Humans can visually track objects mostly effortlessly. However, it is hard for a computer to track a fast moving object under varying illumination and occlusions, in clutter, and with varying appearance in camera projective space due to its relaxed rigidity or change in viewpoint. Since a generic, precise, robust, and fast tracker could trigger many applications, object tracking has been a fundamental problem of practical importance since the beginnings of computer vision. The first contribution of the thesis is a computationally efficient approach to tracking objects of various shapes and motions. It describes a unifying tracking system that can be configured to track the pose of a deformable object in a low or high-dimensional state-space. The object is decomposed into a chained assembly of segments of multiple parts that are arranged under a hierarchy of tailored spatio-temporal constraints. The robustness and generality of the approach is widely demonstrated on tracking various flexible and articulated objects. Haar-like features are widely used in tracking. The second contribution of the thesis is a parser of ensembles of Haar-like features to compute them efficiently. The features are decomposed into simpler kernels, possibly shared by subsets of features, thus forming multi-pass convolutions. Discovering and aligning these kernels within and between passes allows forming recursive trees of kernels that require fewer memory operations than the classic computation, thereby producing the same result but more efficiently. The approach is validated experimentally on popular examples of Haar-like features

Made available in DSpace on 2014-12-17T14:56:07Z (GMT). No. of bitstreams: 1 JesseHNB_DISSERT.pdf: 2206144 bytes, checksum: 191ca3ce00f97e4019b5bdb2bc9ab914 (MD5) Previous issue date: 2012-10-18 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / The vision is one of the five senses of the human body and, in children is responsible for up to 80% of the perception of world around. Studies show that 50% of children with multiple disabilities have some visual impairment, and 4% of all children are diagnosed with strabismus. The strabismus is an eye disability associated with handling capacity of the eye, defined as any deviation from perfect ocular alignment. Besides of aesthetic aspect, the child may report blurred or double vision . Ophthalmological cases not diagnosed correctly are reasons for many school abandonments. The Ministry of Education of Brazil points to the visually impaired as a challenge to the educators of children, particularly in literacy process. The traditional eye examination for diagnosis of strabismus can be accomplished by inducing the eye movements through the doctor s instructions to the patient. This procedure can be played through the computer aided analysis of images captured on video. This paper presents a proposal for distributed system to assist health professionals in remote diagnosis of visual impairment associated with motor abilities of the eye, such as strabismus. It is hoped through this proposal to contribute improving the rates of school learning for children, allowing better diagnosis and, consequently, the student accompaniment / A vis?o ? um dos cinco sentidos do corpo humano e, em crian?as, ? respons?vel por at? 80% da percep??o do mundo ao redor. Estudos revelam que 50% das crian?as com m?ltiplas defici?ncias possuem alguma defici?ncia visual, sendo que 4% de todas as crian?as s?o diagnosticadas com estrabismo. O estrabismo ? uma defici?ncia ocular associada ? capacidade de movimenta??o dos olhos, caracterizada por qualquer desvio no alinhamento ocular perfeito. Al?m do aspecto est?tico, a crian?a pode relatar vista emba?ada ou dupla . Problemas oftalmol?gicos n?o diagnosticados corretamente s?o motivos de muitos abandonos da escola. O Minist?rio da Educa??o do Brasil aponta as defici?ncias visuais como um grande desafio aos educadores de crian?as, principalmente no processo de alfabetiza??o. O exame oftalmol?gico tradicional para diagn?stico do estrabismo pode ser realizado induzindo os movimentos oculares atrav?s de instru??es do m?dico ao paciente. Esse procedimento pode ser reproduzido com aux?lio computacional atrav?s da an?lise de imagens capturadas em v?deo. Este trabalho apresenta uma proposta de sistema de teleoftalmologia para auxiliar profissionais da sa?de no diagn?stico a dist?ncia de defici?ncias visuais associadas ? capacidade motora dos olhos, como o estrabismo. Espera-se atrav?s deste trabalho contribuir diretamente para a melhoria dos ?ndices do aprendizado escolar infantil, permitindo melhores condi??es de diagn?stico e, consequentemente, acompanhamento do aluno

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 detectors. We propose two techniques to this end. Thirdly, we present a detailed large-scale study on self-updating face recognition systems in an attempt to answer if continuously changing facial appearance can be learnt automatically. / L'objectiu d'aquesta tesi és sobre biometria facial, específicament en els problemes de detecció de rostres i reconeixement facial. Malgrat la intensa recerca durant els últims 20 anys, la tecnologia no és infalible, de manera que no veiem l'ús dels sistemes de reconeixement de rostres en sectors crítics com la banca. En aquesta tesi, ens centrem en tres sub-problemes en aquestes dues àrees de recerca. En primer lloc, es proposa mètodes per millorar l'equilibri entre la precisió i la velocitat del detector de cares d'última generació. En segon lloc, considerem un problema que sovint s'ignora en la literatura: disminuir el temps de formació dels detectors. Es proposen dues tècniques per a aquest fi. En tercer lloc, es presenta un estudi detallat a gran escala sobre l'auto-actualització dels sistemes de reconeixement facial en un intent de respondre si el canvi constant de l'aparença facial es pot aprendre de forma automàtica.