National Repository of Grey Literature 23 records found  previous11 - 20next  jump to record: Search took 0.01 seconds. 
Classifiaction algorithms for face-based identification systems
Hegr, Vojtěch ; Křupka, Aleš (referee) ; Malach, Tobiáš (advisor)
The thesis deals with the research of classification algorithms for face-based identification. The aim is to implement algorithms into an existing system for face recognition and the evaluation of the impect of individual classifiers. According to the survey of face recognition methods the following classifiers were chosen for implementation: K - Nearest Neighbours (K-NN), Support Vector Machines (SVM) and the Neural Networks. These classification algorithms were implemented in C++ (Microsoft Visual Studio 2010) using the open source library OpenCV. Furthermore, the IFaVID database and the methodology used to test the implemented algorithms were introduced.
Acceleration of Face Recognition Algorithm with Neural Compute Stick 2
Mičánková, Eva ; Beran, Jan (referee) ; Goldmann, Tomáš (advisor)
This thesis focuses on the issue of facial recognition in a face image using neural networks and its acceleration. It provides an overview of previously used techniques and addresses the use of currently dominant convolutional neural networks to solve this issue. The work also focuses on acceleration mechanisms that can be used in this area. Based on the knowledge of the issue, a system based on the concept of edge computing was created, which can be used as a home security system connected to an IP camera, which sends a notification about the presence of an unknown person in a guarded area.
Detection and Analysis of Violators in the Monitored Area
Sadílek, Jakub ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
The aim of this thesis is to create an internet application for detection and analysis of violators in the monitored area. Such an application then can be used for automated processing of records from security cameras or other captured videos from the guarded area. The first part of the work is focused on the theory of neural networks for object detection and classification in the image and recognition of people by their face. The next part describes used technologies for application development. The result is a client-server application with the possibility of configuration of processing, which allows detection of violators, identification of persons, object tracking and counting, path drawing, definition of the monitored area, usage of own detector, etc. Processed videos at the end can be played, downloaded or together with a list of detected violators shared on the internet via link.
Face Recognition in Security and Surveillance Camera Systems
Malach, Tobiáš ; Říha, Kamil (referee) ; Hudec,, Róbert (referee) ; Poměnková, Jitka (advisor)
Tato práce se zabývá zvýšením úspěšnosti rozpoznávání obličejů v dohledových CCTV systémech a systémech kontroly vstupu. K dosažení tohoto cíle je využit nový přístup - optimalizace vzorů obličejů. Optimalizace tvorby vzorů umožní vytvořit vzory, které zajistí zvýšení úspěšnosti rozpoznání. Měření a další zvyšování úspěšnosti rozpoznávání obličejů vyžaduje naplnění následujících dílčích cílů této práce. Prvním cílem je návrh a sestavení reprezentativní databáze obličejů, která umožní dosáhnout věrohodných a statisticky spolehlivých výsledků rozpoznávání obličejů v dohledových CCTV systémech a systémech kontroly vstupu. Druhým cílem je vytvoření metodiky pro statisticky spolehlivé porovnání výsledků, která umožní konstatování relevantních závěrů. Třetím cílem je výzkum tvorby vzorů a jejich optimalizace. Z dosažených výsledků vyplývá, že optimalizace tvorby vzorů zvyšuje úspěšnost rozpoznávání v uvedených a náročných aplikacích typicky o 4-8%, a v některých případech i 15%. Optimalizace tvorby vzorů přispívá použitelnosti rozpoznávání obličejů v uvedených aplikacích.
Biometric Gateway Using Camera to Identify People
Jelen, Vilém ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
Biometric gateways are used to quickly and accurately identify people. Of the biometric characteristics, iris, face and fingerprints are commonly used. By combining them, better identification results can be achieved. The aim of this thesis is to create such a biometric gateway together with the control application. A combination of iris of both eyes and face is used, which is captured by cameras from three angles to increase accuracy. Neural networks are used to detect and extract face features. Iris recognition is realized using Daugman's algorithm.
Face Recognition
Benda, Tomáš ; Hradiš, Michal (referee) ; Smrž, Pavel (advisor)
This thesis deals with human recognition on a videorecording. Convolution neural network was used for face recognition, from which we will get multidimensional vector, which will allow to determine person’s identity. There are demands imposed on the system, for it to be able to work in real time and could be used for example for person recognition at various conferences, or as a part of security system. Whole system is written in Python language. Part of this thesis is dataset in form of videorecords with persons.
Classifiaction algorithms for face-based identification systems
Hegr, Vojtěch ; Křupka, Aleš (referee) ; Malach, Tobiáš (advisor)
The thesis deals with the research of classification algorithms for face-based identification. The aim is to implement algorithms into an existing system for face recognition and the evaluation of the impect of individual classifiers. According to the survey of face recognition methods the following classifiers were chosen for implementation: K - Nearest Neighbours (K-NN), Support Vector Machines (SVM) and the Neural Networks. These classification algorithms were implemented in C++ (Microsoft Visual Studio 2010) using the open source library OpenCV. Furthermore, the IFaVID database and the methodology used to test the implemented algorithms were introduced.
Face recognition
Maňkoš, Richard ; Mézl, Martin (referee) ; Kolář, Radim (advisor)
This diploma thesis deals with face recognition in digital pictures. The first part describes biometry and, shortly, characterizes biometrical methods which are the most oftenly used. In the second part is described the approach of face recognition in a picture. Specifically, it is described the method for face detection - Viola-Jones and method for face recognition - PCA, which will be implemented in Matlab. The last part, which is practical, describes the scheme for video-sequence recording, implementation of the PCA method in Matlab and discussion of the achieved results.
3D Face Reconstruction Based on 2D Image
Karhánek, Martin ; Láník, Aleš (referee) ; Částek, Petr (advisor)
This work deals with procedures that enables you reconstruct 3D face from a 2D picture. It describes ways to analyze an input picture, such as a face and facial features localization, on which this reconstruction builds. A reader is getting into a morphable model, its creation from static database data and and its usage on a reconstruction, more detailed later on, this morphable model is a building block of mentioned methods. This work contains also an algorithm implementation based on this model.
Recognizing Faces within Image
Svoboda, Pavel ; Žák, Pavel (referee) ; Švub, Miroslav (advisor)
The essence of face recognition within the image is generally computer vision, which provides methods and algorithms for the implementation. Some of them are described just in this work. Whole process is split in to three main phases. These are detection, aligning of detected faces and finally its recognition. Algorithms which are used to applied in given issue and which are still in progress from todays view are mentioned in every phase. Implementation is build up on three main algorithms, AdaBoost to obtain the classifier for detection, method of aligning face by principal features and method of Eigenfaces for recognizing. There are theoretically described except already mentioned algorithms neural networks for detection, ASM - Active Shape Models algorithm for aligning and AAM - Active Appearance Model for recognition. In the end there are tables of data retrieved by implemented system, which evaluated the main implementation.

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