National Repository of Grey Literature 6 records found  Search took 0.00 seconds. 
Face Detection and Identification
Konôpková, Júlia ; Drahanský, Martin (referee) ; Váňa, Jan (advisor)
This work is focused on the problematic of face detection and identification in photography. The introduction is devoted to the most popular methods with briefly descriptions of their principles and rules. Within the practical part of this work we implement and test on free available databases the several of these methods. In the conclusion we evaluate the results and addition of this whole work.
Automatic Face Recognition in Real Environment
Kičina, Pavol ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This master‘s thesis describes the identification faces in real terms. It includes an overview of current methods of detection faces by the classifiers. It also includes various methods for detecting faces. The second part is a description of two programs designed to identify persons. The first program operates in real time under laboratory conditions, where using web camera acquires images of user's face. This program is designed to speed recognition of persons. The second program has been working on static images, in real terms. The main essence of this method is successful recognition of persons, therefore the emphasis on computational complexity. The programs I used a staged method of PCA, LDA and kernel PCA (KPCA). The first program only works with the PCA method, which has good results with respect to the success and speed of recognition. In the second program to compare methods, which passed the best method for KPCA.
Face Identification on Android Platform
Karhánek, Martin ; Řezníček, Ivo (referee) ; Láník, Aleš (advisor)
This work describes ways to use a person identification based on faces on mobile devices with Android platform. A reader is introduced into a structure of this system and a way to create applications for it. Besides, there are also methods usable to the face identification. Some of these methods (used in an implementation) are described in more detail. This work also contains a description of model AAM (Active Appearance Model) for implementing in mobile devices and evaluation of used algorithms results.
Face Detection and Identification
Konôpková, Júlia ; Drahanský, Martin (referee) ; Váňa, Jan (advisor)
This work is focused on the problematic of face detection and identification in photography. The introduction is devoted to the most popular methods with briefly descriptions of their principles and rules. Within the practical part of this work we implement and test on free available databases the several of these methods. In the conclusion we evaluate the results and addition of this whole work.
Face Identification on Android Platform
Karhánek, Martin ; Řezníček, Ivo (referee) ; Láník, Aleš (advisor)
This work describes ways to use a person identification based on faces on mobile devices with Android platform. A reader is introduced into a structure of this system and a way to create applications for it. Besides, there are also methods usable to the face identification. Some of these methods (used in an implementation) are described in more detail. This work also contains a description of model AAM (Active Appearance Model) for implementing in mobile devices and evaluation of used algorithms results.
Automatic Face Recognition in Real Environment
Kičina, Pavol ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This master‘s thesis describes the identification faces in real terms. It includes an overview of current methods of detection faces by the classifiers. It also includes various methods for detecting faces. The second part is a description of two programs designed to identify persons. The first program operates in real time under laboratory conditions, where using web camera acquires images of user's face. This program is designed to speed recognition of persons. The second program has been working on static images, in real terms. The main essence of this method is successful recognition of persons, therefore the emphasis on computational complexity. The programs I used a staged method of PCA, LDA and kernel PCA (KPCA). The first program only works with the PCA method, which has good results with respect to the success and speed of recognition. In the second program to compare methods, which passed the best method for KPCA.

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