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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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Faces recognition as a distinctive cognitive process
Fišer, Ondřej ; Fuchs, Roman (advisor) ; Pokorný, Šimon (referee)
Facial recognition has been a major scientific topic. What particular cognitive process is responsible for recognition was a great unknown. Now, scientists are most inclined to the theory of holistic facial perception that we perceive the face as a whole. For successful face recognition it is necessary to pay attention to individual components and their configuration. Thanks to this approach, a person is an expert on faces and can obtain many types of information from them in a short time. Behavioral and neurological evidence supported the theory of holistic facial perception. The main behavioral tasks that support holistic facial perception are three: part-whole task, face inversion task, and composite task. The first two showed that face recognition negatively affects both the manipulation of individual components and their configuration. The composite task then shows that we are not able to perceive individual parts of the face independently. Holistic perception in animals has not been unequivocally confirmed, but for animals the face is as important as for humans. Moreover, the possibility of applying holistic perception to objects other than faces is currently being pointed out. Holistic perception today appears to be a robust type of perception applicable to various stimuli that meet the...
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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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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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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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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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Experiments with Face Thermograms
Kočár, Radek ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
This thesis describes characteristics and usage of face thermograms. First part of thessis introduces historcal development of thermal imaginery. Thesis continues with theory for thermographic measurement techniques, physical theory and methods for face detection, localization and recognition. Last chapter describes experiments with thermograms and possibilities for application of thermography.
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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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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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