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Biometric 2D face recognition from camera system placed on a quadrocopter
Mikundová, Lea ; Mráček, Štěpán (referee) ; Drahanský, Martin (advisor)
This Bc. thesis is devoted to face recognization from camera system placed on a quadrocopter. The teoretical part is about the most used methods for detection and face recognition and their comparison. The next part is about motion capturing from quadrocopter. Practical part of thesis is devoted to implementation of algorithms for face detection and recognization by OpenCV library and evaluation of algorithm in respect to distance and angle of quadrocopter due to captured person.
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Face Recognition
Duban, Michal ; Beran, Vítězslav (referee) ; Smrž, Pavel (advisor)
This Bachelor's thesis aimed to develop an application, executable by the robot PR2, capable of automatical recognizing and memorizing human faces which are displayed successively on video recorded by cameras placed on the robot.
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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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Image processing using Android device
Korchakov, Sergei ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
This master’s Thesis focuses on image processing on Android platform and development of an application, that is able to do face detection and recognition in real scene. Thesis gives highlight of modern algorithms of face detection. It first examines and compares the standard features of Android platform (FaceDetector a FaceDetectionListener) and JJIL, OpenIMAJ, OpenCV libraries experiment, and presents the results. For purposes of face recognition was selected OpenCV library. Three different algorithms of identification were tested: FisherFaces, EigenFaces a Local Binary Patterns Histograms. Based on performance comparison best methods were implemented in developed application.
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Person Identification
Ťapuška, Tomáš ; Zuzaňák, Jiří (referee) ; Hradiš, Michal (advisor)
This master's thesis is about the most known methods for face recognition. There are described their advantages and disadvantages. This work is specialized at holistic methods for face recognition, which are working with 2D pictures of people. I implemented the automatic system for face recognition according to digital picture of face. There was, in this system, implemented these methods: KNN (K nearest neighbour), PCA (Principal component analysis) and LDP (Linear doscriminant projection). There was done some tests to compare implemented methods. The tests was done on the pictures from dataset FERET. In the conclusion of this text are considered implemented approaches and is marked the best method for face recognition from implemented.
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Detection and Recognition of Dominant Face Features
Švábek, Hynek ; Láník, Aleš (referee) ; Chmelař, Petr (advisor)
This thesis deals with the increasingly developing field of biometric systems which is the identification of faces. The thesis deals with the possibilities of face localization in pictures and their normalization, which is necessary due to external influences and the influence of different scanning techniques. It describes various techniques of localization of dominant features of the face such as eyes, mouth or nose. Not least, it describes different approaches to the identification of faces. Furthermore a it deals with an implementation of the Dominant Face Features Recognition application, which demonstrates chosen methods for localization of the dominant features (Hough Transform for Circles, localization of mouth using the location of the eyes) and for identification of a face (Linear Discriminant Analysis, Kernel Discriminant Analysis). The last part of the thesis contains a summary of achieved results and a discussion.
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Deep learning based face recognition in real conditions
Horňáková, Veronika ; Kříž, Petr (referee) ; Přinosil, Jiří (advisor)
This bachelor thesis explores the area of face recognition using deep learning technique. Face recognition is used for two main reasons: verification and identification. In this thesis we describe the techniques of deep learning, mostly the convolutional neural networks, which are the most significant method for processing images - detection, classification and segmentation of the image. The process of face recognition is divided into four main steps: face detection, face selection, face extraction and face classification. We chosen three of the existing programs for face recognition (OpenFace, FaceNet and Face_Recognition), which are described in this thesis, in particular the principle of the human face recognition. Thanks to the tests with the data set of Labeled Faces in the Wild (LFW) we could specify the accuracy and the time requirement of each application. Testing of FaceNet and Face_Recognition ran on real data with face detection in video with complicated conditions. The test compares two images and tries to determine if is the same person. The test results are show in graph and table.
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Video database for face feature recognition
Stříteský, Jan ; Říha, Kamil (referee) ; Vlach, Jan (advisor)
This work compares face databases freely accessible on the Internet which are suitable for the testing of developed algorithms for facial features recognition in a picture. In the course of the work’s project a new face video database was created, encompassing a total of 51 samples. The video database includes a simple application suitable for searching through its contents. In order to limit the size of the video database, compression of individual picture samples was conducted. The created video database can be implemented for testing algorithms for facial features recognition (e.g. face detection in a video, identification of a person, detection of eye blinking, speech recognition).
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Face Reader
Bučko, Peter ; Juránek, Roman (referee) ; Beran, Vítězslav (advisor)
This thesis deals with computer face recognition. Methods of Components Analysis (PCA), Linear Discriminant Analysis (LDA) and Elastic Bunch Graph Matching (EBGM) are described here. Aim of this thesis is creation of a demonstration aplication for a face recognition. Moreover I test PCA and LDA methods to find out, how accurate it can be and how can be affected by changing of parameters, such as size of a database and picture count per person.
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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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