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Research in the field of biometric detection and recognition of individuals using facial image data
Goldmann, Tomáš ; Štruc, Vitomir (oponent) ; Yoon, Sang Min (oponent) ; Drahanský, Martin (vedoucí práce)
Biometric recognition has long since become a common concern in various fields of study, including forensics, anthropometry, biometrics, and computer science. This thesis focuses on the development of an approach to create datasets for the evaluation of face recognition algorithms, with an emphasis on the preservation of facial features. Such datasets open up new possibilities for the evaluation of face recognition algorithms, which were previously hindered by the limited sample size of the datasets usually used. Through extensive research in the field of face recognition algorithms and modern neural network techniques, algorithms for face detection and recognition on embedded devices have been developed. These algorithms are based on the EfficientNet feature extractor.
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Detecting Presentation Attacks Using Face Spoofing
Homola, Tomáš ; Orság, Filip (oponent) ; Goldmann, Tomáš (vedoucí práce)
Face detection is one of the most important and widespread methods of verifying a person's identity. However, this method also raises concerns about privacy and security. It is important to be aware of the dangers it brings and constantly develop the necessary means to protect against them. This thesis aims to explain the issue of face spoofing, the threat that arises from a successful attacker's attempt at spoofing, and the detection of these spoofs using algorithms.
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Počítačová hra s umělou inteligencí
Ludrovan, Tomáš ; Goldmann, Tomáš (oponent) ; Orság, Filip (vedoucí práce)
Práce se zabývá vývojem počítačové hry pro více hráčů a prozkoumáním možností použití umělé inteligence pro implementaci entit řízených počítačem. Hra je psána v programovacím jazyce C++ a využívá knihovnu SDL2 pro realizaci uživatelského vstupu a výstupu na obrazovku. Mimo jiné jsou zde také popsány různé běžně používané algoritmy z oblasti umělé inteligence, které hra využívá buď přímo, nebo jejich upravenou variantu.
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A Reduced Neural Network for Classifying the Presence of People in an Image
Stanček, Rastislav ; Rydlo, Štěpán (oponent) ; Goldmann, Tomáš (vedoucí práce)
This thesis focuses on the topic of computer vision, more specifically, on classifying people's presence in image data. The goal is to create a reduced neural network utilizing knowledge distillation. Object classification and detection is a computationally an expensive operation. A student model created utilizing knowledge distillation shows equivalent accuracy while being smaller and having better inferencing speed compared to the teacher model. Such model can be interdisciplinarily utilized on end devices having relatively low computational capabilities.
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Detekce živosti a identifikace dlaně
Kala, Adam ; Goldmann, Tomáš (oponent) ; Sakin, Martin (vedoucí práce)
Tato bakalářská práce je zaměřena na detekci živosti lidské ruky a její identifikaci z multispektrálních snímků. Hlavním cílem práce je rozpoznávání živé ruky a jejích falzifikátů na základě námi získaných informací, nález markantů pro identifikaci dlaně a jejich použití. V práci jsou popsány techniky na ořez zájmové oblasti, na extrakci charakteristických znaků z dlaně a následná detekce živosti a identifikace osoby. Úspěšnost detekce živosti dosáhla přes 90% a identifikace osob s mírou chybného přijetí (FAR) menší než 2% pro zvolené datové sady.
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Person Recognition Based on Anthropometric Proportions
Šimún, Samuel ; Semerád, Lukáš (oponent) ; Goldmann, Tomáš (vedoucí práce)
This bachelor thesis focuses on the potential use of biometrics and machine learning. It discusses in detail anthropometric characteristics, their evolution and the potential of using these characteristics for person identification. It analyzes the potential uses of machine learning and what technologies exist for extracting a person's pose from an image for outputting the pose in the second dimension and in the third dimension. Also, the thesis describes and implements specific methods that use anthropometric features for person identification.
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Aplikace pro autentizaci osob na základě snímků sítnice
Moncz, Oliver ; Goldmann, Tomáš (oponent) ; Kavetskyi, Andrii (vedoucí práce)
Tato práce se zaobírá problémem autentizace osob na základě snímků sítnice. Hlavním cílem je navrhnout algoritmus, který dokáže porovnat snímek sítnice s registrovanými snímky v databázi. Výstupem je potom určení totožnosti s mírou jistoty. Dalším cílem bylo vytvořit aplikaci, která přes jednoduché grafické uživatelské prostředí umožní provádět zmíněné operace. Nakonec jsou vyhodnoceny výsledky a porovnány s již existujícími řešeními. Navržený autentizační systém dosáhl průměrné přesnosti 72,46 % pro datasety DRIVE a STARE, pro dataset FIRE dosáhl 78,9 %.
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An Application for Analyzing the Resilience of Facial Recognition Algorithms against a Deepfake Image
Kučík, Adam ; Pleško, Filip (oponent) ; Goldmann, Tomáš (vedoucí práce)
This thesis focuses on creating an application capable of determing whether a given image is deepfake or not. The application is created by using the convolutional neural network vgg-net. Part of the work is to create a Siamese neural network and test if it is suitable for detecting deepfake images. Several configurations of vgg16 and vgg19 networks are created within the thesis. Each configuration contain tables with the success rates of individual models agains our created deepfake dataset. The thesis also includes a section where we discuss deepfake algorithms that are open-source and describe the work with them. The entire application is implemented in Python using the TensorFlow library.
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Laser Line Profilometry
Kugler, Jan ; Goldmann, Tomáš (oponent) ; Malaník, Petr (vedoucí práce)
A profilometer is a device used to measure the geometry of a surface. They vary significantly in size, precision and speed of measurement, and price. The aim of this thesis is to create a software library and end-user application for a simple laser-camera setup. A mathematical model of the system is developed and used to determine position of surface features in real space. The demonstration application allows the user to view the raw camera input, the processed image, as well as the resulting profile.
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The impact of facial expressions on 3D face recognition.
Kováč, Peter ; Goldmann, Tomáš (oponent) ; Pleško, Filip (vedoucí práce)
The thesis "The impact of facial expressions on 3D face recognition" focuses on studying the effect of facial expressions on the accuracy of 3D face recognition. The first chapters explore various 3D modeling techniques and their applications, including 3D Morphable Models (3DMMs), blendshape models, and neural network-based methods like FLAME (Faces Learned with an Articulated Model and Expressions). The thesis then presents a new approach for reconstructing 3D face models from 2D images and proposes an evaluation framework to measure the impact of facial expression changes on 3D face recognition. Experimental results demonstrate how different expressions, such as anger, happiness, and fear, influence recognition accuracy. The findings of this work contribute to a deeper understanding of facial expressions’ role in 3D face recognition and propose potential improvements for enhancing recognition systems.
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