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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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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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Face recognition in digital images
Hauser, Václav ; Přinosil, Jiří (referee) ; Říha, Kamil (advisor)
This master thesis deals with the detection and recognition of faces in the image. The content of this thesis is a description of methods that are used for the face detection and recognition. Method described in detail is the principal component analysis (PCA). This method is subsequently used in the implementation of face recognition in video sequence. In conjunction with the implementation work describes the OpenCV library package, which was used for implementation, specifically the C ++ API. Finally described application tests were done on two different video sequences.
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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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Application of Neural Accelerators on Rapsberry PI
Barna, Kristian ; Sekanina, Lukáš (referee) ; Vašíček, Zdeněk (advisor)
The presented bachelor thesis deals with the statistical evaluation of performance for hardward accelerator of deep neural networks. Describes convolutional neural networks along with mathematical calculations. Explains their acceleration and conversion to a format suitable for the Intel Movidius NCS accelerator. 8 hardware platforms and 22 neural network difficulties were compared experimentally. Up to 105-fold improvement was demonstrated in isolated inference of the MobileNetV2 network for the Raspber Pi platform using an accelerator. Performance between the tested platforms was also evaluated from an energy point of view. The application of facial identity demonstrated the conditions during real use. Possible limits of CNN acceleration on power-limited devices (Raspberry Pi) have been uncovered, especially due to improper selection of input image resolution. All measurements were evaluated by statistical procedures.
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Face Detection and Recognition
Ponzer, Martin ; Janáková, Ilona (referee) ; Horák, Karel (advisor)
This paper discusses problems of computer vision, which deals with face detection and recognition in image and video sequence at real time. All methods are designed for color images and are based on skin detection on the basis of information of human skin color. For skin detection is used very effective method Gaussian distribution. All of the areas, which have human skin color, are classified. This classification specifies, which area is or isn’t face. For face detection is used correlation method, complete with eigenfaces method. All areas classified as a face are subsequently recognized by the eigenfaces method. Result of recognition phase is information about human identity.
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Human Presence Detection and Applications in Smart Home Environments
Dostál, Pavel ; Juránek, Roman (referee) ; Černocký, Jan (advisor)
Práce se zabývá studiem detekce a rozpoznávání člověka a následnou implementací v prostředí softwaru Home Manager, což je projekt simulující chytrý dům s intelligentními zařízeními. Rozšíření o funkcionalitu rozpoznání uživatelů a narušitelů umožní lépe přizpůsobit chování zařízení preferencím jednotlivých osob. Použití rozpoznávání je demonstrováno na ukázce ovládání klimatizace v místnostech podle přítomnosti uživatelů.
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Social Network from Photo Gallery
Polesný, Ondřej ; Přibyl, Bronislav (referee) ; Mlích, Jozef (advisor)
This thesis deals with recognition of persons and their relationships from static images and presents ways in which these information can be used. That includes methods for detection and recognition of faces, presentation of photos in web-based gallery and methods for recognition of relationships between photographed persons. Part of this thesis is evaluation of the results, both in terms of program success in automated operations by establishing a set of test data with known relationships between people, and in terms of efficiency and functionality of the system for end users.
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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.
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