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Facial Recognition in Video and its Applications in Law Enforcement
Fabián, Jan ; Šťastná, Dagmar (referee) ; Šedrlová, Magdalena (advisor)
This bachelor thesis aims to describe the facial recognition technology and its use in practice. In recent years, facial recognition technology became a heavily discussed topic, whether in connection with the deployment of this technology in China or due to its general potential for law enforcement. Facial recognition technology is a perfect example of a two-sided coin, as it brings many new possibilities of crime prevention etc. but also has the risk of being used to invade personal privacy. This thesis is based on a literature survey of some of the available resources dealing with this topic. It focuses on the history of this technology, methods used by facial recognition and mentions some examples of the use of video-based facial recognition in practice along with the social risks of the application of this technology.
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Intelligent Access Terminal Using ESP32 Platform
Pomykal, Šimon ; Vašíček, Zdeněk (referee) ; Šimek, Václav (advisor)
The aim of this thesis is to design cheap intelligent access control system based on esp32. This system is designed for use in family houses, flats, garages, gardens etc. The designed system is composed of access control terminal module which uses fingerprint reader to authenticate people and of camera modules which monitor the area of entry These modules are connected to cloud using AWS IoT Core. Another part of the system is a cloud application which evaluates data from the system. The acces control system is meant to be part of a home security system, but can be used independently to some extent.
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Creation of the Database with Different Face Gestures and Realization of Experiments
Marešová, Marcela ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
This paper describes methods used in tools for recognition persons by faces. (face recognition). It focuses on change of face expression factor, which influence this process. This paper deals with creation of the database with different face gestures for testing recognition of faces affected by this factor. Next part was creation pictures of different face gestures by the help of software and their tests. Conclusions of the experiment mentioned in this paper reflect weightiness of this problem and suggests possible resolution.
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Search for People in Recordings from Security Cameras
Jezerský, Matouš ; Hradiš, Michal (referee) ; Smrž, Pavel (advisor)
This thesis deals with the design and implementation of a system, which allows to search for and recognize people in video recordings. The presented design is based on a preceding research in theory relating to the topics of face and people recognition. Furthermore, the system design is implemented using convolutional neural networks for face recognition, while the implementation primarily utilizes the libraries dlib and OpenFace. The design and implementation use parallelization and distribution of tasks among multiple devices to reduce computation time, while also bearing in mind the practical applications of such system, such as working with limited amounts of available information regarding the person we seek. The precision of people detection and recognition of the implemented system is about 70% to 80%, based on the performed task. Among other uses, the system can be utilized to find a particular person in a video recording, to estimate the number of passes through the monitored space of one person, or the number of passes in total, or to find unknown people in the monitored space.
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Tracking and Recognition of People in Video
Šajboch, Antonín ; Hradiš, Michal (referee) ; Smrž, Pavel (advisor)
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.
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Dataset generation for specific cases of face recognition
Kolmačka, Tomáš ; Kolařík, Martin (referee) ; Rajnoha, Martin (advisor)
The diploma thesis deals with current problems of person identification and deep learning. Furthermore, the work deals mainly with obtaining quality and diverse data that are used to train deep learning with convolutional neural networks for face recognition. There is very little public access to such data, so the practical part focuses on creating the MakeHuman plugin that will generate a database of random face images. It is possible to generate faces according to five different scenarios in which purely random faces or faces where the same can be seen with modifications such as different hair, beard, hat, glasses and more are created. The scenarios also allow you to generate faces with some expressions or faces as they age. You can set some parameters that give the appearance of the resulting database in the plugin. This can include face images from different angles of rotation, zooming and lighting.
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Recurrent Neural Networks in Computer Vision
Křepský, Jan ; Řezníček, Ivo (referee) ; Španěl, Michal (advisor)
The thesis concentrates on using recurrent neural networks in computer vision. The theoretical part describes the basic knowledge about artificial neural networks with focus on a recurrent architecture. There are presented some of possible applications of the recurrent neural networks which could be used for a solution of real problems. The practical part concentrates on face recognition from an image sequence using the Elman simple recurrent network. For training there are used the backpropagation and backpropagation through time algorithms.
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Convolutional Neural Networks for Emotion Recognition
Jileček, Jan ; Najman, Pavel (referee) ; Hradiš, Michal (advisor)
Convolutional neural networks are used for various tasks, but foremost in machine learning, in which they excel. This work is going to introduce some existing frameworks, other algorithms for recognition and then we describe the training dataset creation and the model for emotion recognition training process. Mentioned model has accuracy of 60%. It is used for emotion statistics retrieval from movie trailers. Model for genre recognition is created from those statistics and then finally used in our application for genre recognition of the input trailer, with best accuracy of 47%.
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The posibilities of the use of facial recognition technology in the context of personal data protection in the EU
Soukupová, Jana ; Svobodová, Magdaléna (advisor) ; Vondráčková, Aneta (referee)
The Possibilities of the Use of Facial Recognition Technology in the Context of Personal Data Protection in the EU Abstract This thesis focuses on the data protection connected to the use of facial recognition technology in the EU. In particular, the purpose of the thesis is to assess under which circumstances and conditions the use of this technology complies with the GDPR. Marginally, the thesis addresses the risks and benefits of facial recognition technology. The thesis is divided into three parts. The first part examines the general data protection framework in the EU, with an emphasis on the protection of biometric data. The aim of this part is to outline the main legal background regarding the protection of biometric data and the general principles of data processing. In particular, the author criticizes the legal definition of biometric data, which does not correspond to the technological reality, and which may be problematic in the case of the application of Article 9 of the GDPR. The second part of the thesis is devoted to facial recognition technology itself, its different types, and applications. An understanding of the technology itself is crucial within this thesis for the correct application of the legal framework. The author also finds it necessary to examine the reasons why this technology...
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The role of the face and the body size in predators' recognition by untrained birds
Fišer, Ondřej ; Fuchs, Roman (advisor) ; Petrusková, Tereza (referee)
The face plays an extremely important role in human communication. It enables individual recognition and provides other information about the person, such as social or emotional information. Human psychology has shown that face recognition uses a specific cognitive process called holistic processing. In recent decades, it has been shown to play an important role in animal communication as well. In the first part of my thesis, I tested whether changing the uniform configuration of a bird's face would affect the ability of the red-backed shrike (Lanius collurio) to recognize a potential predator. Due to unfavourable conditions in both breeding seasons when the experiments were conducted, no firm conclusions can be drawn from the results. They only suggest that the shrike perceives the configuration changes. An essential characteristic of all predators is their size, which affects the ability of prey to defend themselves. Several studies have already found that birds discriminate between different predators of different sizes. In the second part of my thesis, I evaluated experiments in which shrikes were exposed to dummies of two predator species with modified size. The shrikes responded with less aggression to the enlarged jays, whereas aggression increased only slightly to the shrunken crows. Thus,...
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