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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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Recognition of Face Thermoscans
Váňa, Jan ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
Images of human face are one of the most used biometric features in automatic identification. This article presents an approach which uses face images in thermal (infrared) spectrum for purpose of important face features (eyes position, head rotation) detection and identification.
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Accelerating Face Anti-Spoofing Algorithms
Beňuš, Ondřej ; Havel, Jiří (referee) ; Veselý, Karel (advisor)
Tato práce se specializuje na akceleraci algoritmu z oblasti obličejově zaměřených anti-spoofing algoritmů s využitím grafického hardware jakožto platformy pro paralelní zpracování dat. Jako framework je použita technologie OpenCL která umožňuje použití od výkoných stolních počítačů po přenosná zařízení, od různých akcelerátorů jako grafické čipy, či ASIC až po procesory typu x86 bez vazby na konkrétního výrobce či operační systém. Autor předkládá čtenáři rozbor a akcelerovanou implementaci široce používaného algoritmu a dopadu urychlení výpočtu.
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Face recognition in video sequences
Malach, Tobiáš ; Průša,, Zdeněk (referee) ; Slanina, Martin (advisor)
This thesis deals with design, implementation and testing of face recognition system processing video sequences captured by CCTV systems. The use of Local Binary Pattern Histograms (LPBH) and Nearest Neighbor (NN) classifier was suggested according to the survey of face recognition methods. Discrimination power of LBPH features was examined and individual informative features were searched based on Fisher discrimination ratio and mutual correlation. Cluster’s centorid method was utilized for pattern creation because of its best effect on system’s face recognition capability comparing several proposed methods. Software tool for effective face recognition system algorithms performance testing was developed. Video database IFaViD was assembled for training and performance testing of implemented face recognition system.
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