<div><div><div><p>Face redaction is needed by law enforcement and mass media outlets to guarantee privacy. In this thesis, a performance analysis of several face redaction/obscuration methods, such as blurring and pixelation is presented. The analysis is based on various threat models and obscuration attackers to achieve a comprehensive evaluation. We show that the traditional blurring and pixelation methods cannot guarantee privacy. To provide a more secured privacy protection, we propose two novel obscuration methods that are based on the generative adversarial networks. The proposed methods not only remove the identifiable information, but also preserve the non-identifiable facial information (as known as the utility information), such as expression, age, skin tone and gender.</p><p>We also propose methods for change detection in satellite imagery. In this thesis, we consider two types of building changes: 2D appearance change and 3D height change. We first present a model with an attention mechanism to detect the building appearance changes that are caused by natural disasters. Furthermore, to detect the changes of building height, we present a height estimation model that is based on building shadows and solar angles without relying on height annotation. Both change detection methods require good building segmentation performance, which might be hard to achieve for the low-quality images, such as off-nadir images. To solve this issue, we use uncertainty modeling and satellite imagery metadata to achieve accurate building segmentation for the noisy images that are taken from large off-nadir angles.</p></div></div></div>

The master thesis presents an overview of face detection task in color, static images. Face detection term is posed in the context of various branches. Main concepts of face detection and also their relationships are described. Individual approaches are divided into groups and then define in turn. In the thesis is in detail described algorithm AdaBoost, which is selected on the basis of its properties. Especially speed of computation and good detection results are key features. In the scope of this work Viola-Jones detector was implemented. This detector was trained with face pictures from public accessible database. Combination of Viola-Jones detector with simple color detector is described. In the thesis is also presented experiment approach to facial features detection.

This paper discusses problems of computer vision, which deals with face detection and recognition in image and video sequence at real time. All methods are designed for color images and are based on skin detection on the basis of information of human skin color. For skin detection is used very effective method Gaussian distribution. All of the areas, which have human skin color, are classified. This classification specifies, which area is or isn’t face. For face detection is used correlation method, complete with eigenfaces method. All areas classified as a face are subsequently recognized by the eigenfaces method. Result of recognition phase is information about human identity.

This master thesis deals with the detection and recognition of faces in the image. The content of this thesis is a description of methods that are used for the face detection and recognition. Method described in detail is the principal component analysis (PCA). This method is subsequently used in the implementation of face recognition in video sequence. In conjunction with the implementation work describes the OpenCV library package, which was used for implementation, specifically the C ++ API. Finally described application tests were done on two different video sequences.

This thesis is about biometric 3D face recognition . A general biometric system as well as functioning of biometric system are present . Techniques used in 2D and 3D face recognition are described . Finally , an automatic biometric system for 3D face recognition is proposed and implemeted . This system divide face for areas by position of detected landmarks . Particular areas are compared separately . Final system fusion results from Eigenfaces and ARENA algorithms .

The project is focused on methods of obtaining large number of images of human faces. Such database should then serve as a set of data for face detection and recognition by the means of supervised machine learning. The work deals with the basic principles of supervised machine learning and available data sets for this procedure. Project contains proposals of techniques and implementation of algorithms suitable for acquiring images from video and a concept of user interface for semi-automatic acceptation and annotation of located images.

This document introduces the reader to area of face recognition. Miscellaneous methods are mentioned and categorized to be able to understand the process of face recognition. Main focus of this document is on issues of current face recognition and possibilities do solve these inconveniences in order to be able to massively spread face recognition. The second part of this work is focused on implementation of selected methods, which are Linear Discriminant Analysis and Principal Component Analysis. Those methods are compared to each other and results are given at the end of work.

Diplomová práce byla vypracována na studijním pobytu na "Gjovik University College" v Norsku, a je zpracována v angličtině. Tato práce se zabývá rozpoznáváním 3D obličejů. Je zde popsán obecný biometrický systém a také konkrétní postupy používané při rozpoznávání 2D i 3D obličejů. Následně je navžena metoda pro rozpoznávání 3D obličejů. Algoritmus je vyvíjen a testován pomocí databáze Face Recognition Grand Challenge (FRGC). Během předzpracování jsou nalezeny význačné body v obličeji a následně je trojrozměrný model zarovnán do referenční polohy. Dále jsou vstupní data porovnávána s biometrickými šablonami uloženými v databázi, a to je zajištěno využitím tří základních technik pro rozpoznávání obličejů -- metoda eigenface (PCA), rozpoznávání založené na histogramu obličeje a rozpoznávání založené na anatomických rysech. Nakonec jsou jednotlivé metody spojeny do jednoho systému, jehož celková výsledná výkonnost převyšuje výkonnost jednotlivých použitých technik.

The master's thesis deals with detecting and tracking people in the video. To get optimal recognition was used convolution neural network, which extracts vector features from the enclosed frame the face. The extracted vector is further classified. Recognition process must take place in a real time and also with respect are selected optimal methods. There is a new dataset faces, which was obtained from a video record at the faculty area. Videos and dataset were used for experiments to verify the accuracy of the created system. The recognition accuracy is about 85% . The proposed system can be used, for example, to register people, counting passages or to report the occurrence of an unknown person in a building.

This study is based on evaluative longitudinal data of facial development in a group of children from 6 to 12 years. The research used three-dimensional models of the faces of 18 girls and 15 boys that were scanned at yearly intervals. These models were used to follow development of the face and its particular areas including analysis of variability (PCA). Developmental changes were observed for each gender separately as well as for the development of sexual dimorphism. Results were visualized by using superimposed color maps of average faces of a particular age group and maps depicting the statistically significant differences in individual areas. The presented data exhibited growth in the face of both genders, while slightly bigger changes in the form of the face were observed in the boys' samples. For girls and boys the most intensive growth was found in the direction of the width and height of the entire face and the nose, especially in the direction of length. These changes took place throughout the whole studied period of growth, yet more intensive growth was evident for girls beginning at age 10 years and for boys from 11 years onward. Shape changes also occurred with age for both genders: the face gradually narrowed, the cheeks flattened and a more retruded position of the forehead...