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Object Detection in Images
Ptáček, Tomáš ; Šiler, Ondřej (referee) ; Švub, Miroslav (advisor)
This work deals with the problem of object detection in images and describes theoretical backgrounds of detection based on boosting, AdaBoost algorithm and Haar-like features as weak classifiers. Further this work engages in design and implementation of a training and detection application based on OpenCV and wxWidgets libraries. To the end it shows a training and face detection test performed in the implemented application.
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Development of algorithms for digital real time image processing on a DSP Processor
Knapo, Peter ; Sajdl, Ondřej (referee) ; Belgium, Jurgen Baert (MSc), KHBO (advisor)
Rozpoznávanie tvárí je komplexný proces, ktorého hlavným ciežom je rozpoznanie žudskej tváre v obrázku alebo vo video sekvencii. Najčastejšími aplikáciami sú sledovacie a identifikačné systémy. Taktiež je rozpoznávanie tvárí dôležité vo výskume počítačového videnia a umelej inteligencií. Systémy rozpoznávania tvárí sú často založené na analýze obrazu alebo na neurónových sieťach. Táto práca sa zaoberá implementáciou algoritmu založeného na takzvaných „Eigenfaces“ tvárach. „Eigenfaces“ tváre sú výsledkom Analýzy hlavných komponent (Principal Component Analysis - PCA), ktorá extrahuje najdôležitejšie tvárové črty z originálneho obrázku. Táto metóda je založená na riešení lineárnej maticovej rovnice, kde zo známej kovariančnej matice sa počítajú takzvané „eigenvalues“ a „eigenvectors“, v preklade vlastné hodnoty a vlastné vektory. Tvár, ktorá má byť rozpoznaná, sa premietne do takzvaného „eigenspace“ (priestor vlastných hodnôt). Vlastné rozpoznanie je na základe porovnania takýchto tvárí s existujúcou databázou tvárí, ktorá je premietnutá do rovnakého „eigenspace“. Pred procesom rozpoznávania tvárí, musí byť tvár lokalizovaná v obrázku a upravená (normalizácia, kompenzácia svetelných podmienok a odstránenie šumu). Existuje mnoho algoritmov na lokalizáciu tváre, ale v tejto práci je použitý algoritmus lokalizácie tváre na základe farby žudskej pokožky, ktorý je rýchly a postačujúci pre túto aplikáciu. Algoritmy rozpoznávania tváre a lokalizácie tváre sú implementované do DSP procesoru Blackfin ADSP-BF561 od Analog Devices.
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Detection of Wanted People in Video
Bažout, David ; Musil, Petr (referee) ; Beran, Vítězslav (advisor)
The aim of this work is to create a software tool for searching of wanted people in video recordings from surveillance cameras. Wanted people are identified to the system using multiple facial photos. The output consists of information on the occurrence of wanted persons in specific frames. The problem consists of face detection and its subsequent identification task. Experiments with existing approaches on appropriate datasets provide relevant comparisons of method performance under different conditions. Appropriate methods and their optimal settings for this particular task are chosen according to the results of the experiments. The thesis also deals with the design of suitable architecture, research of existing libraries implementing the tested methods and other ways of optimizing the calculation. The result is the implementation of a user application that meets the specified parameters. The application's functionality has been tested on the own dataset simulating real-world conditions.
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Head Pose Estimation and Tracking
Pospíšil, Aleš ; Krajsa, Ondřej (referee) ; Přinosil, Jiří (advisor)
Diplomová práce je zaměřena na problematiku detekce a sledování polohy hlavy v obraze jako jednu s možností jak zlepšit možnosti interakce mezi počítačem a člověkem. Hlavním přínosem diplomové práce je využití inovativních hardwarových a softwarových technologií jakými jsou Microsoft Kinect, Point Cloud Library a CImg Library. Na úvod je představeno shrnutí předchozích prací na podobné téma. Následuje charakteristika a popis databáze, která byla vytvořena pro účely diplomové práce. Vyvinutý systém pro detekci a sledování polohy hlavy je založený na akvizici 3D obrazových dat a registračním algoritmu Iterative Closest Point. V závěru diplomové práce je nabídnuto hodnocení vzniklého systému a jsou navrženy možnosti jeho budoucího zlepšení.
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Automatic People Counting from Panoramic Photography
Blucha, Ondřej ; Kolář, Martin (referee) ; Veľas, Martin (advisor)
This bachelor thesis deals with automatic people counting from panoramic photography. This is very useful for counting large number of people, such as on the stadium or on the concerts. It consists of the two parts. The first one is image stitching, which process the images by the feature-based methods. The second part is people counting using face detection, where were used Viola-Jones detector. The ideal setting of parameters for used methods was experimentally selected.
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Identification of Persons in the Video from Quadcopter
Mojžiš, Tomáš ; Drahanský, Martin (referee) ; Goldmann, Tomáš (advisor)
The aim of this thesis is to make an application capable of recognizing people's faces based on a user-created database in drone footage. The database is made of pictures of people that should be identified in the footage. The output of this application is a video where the demanded people are labeled with their names. Some face detection and recognition state of the art solutions based on neural networks are compared in this work. The final solution consists of the MTCNN detector and a face embedding extractor based on ArcFace. The created multiplatform application allows to recognize people in drone footage even with face width of less than 20 pixels. The final solution was tested on a private dataset comprised of drone footage.
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Visual head motion monitoring
Sieber, Lukáš ; Babinec, Tomáš (referee) ; Richter, Miloslav (advisor)
This bachelor thesis is based on finding of head rotation and position against stationary shoulders from frames captured by web camera in real time. Furthermore the thesis adverts to benefits of using Open CV. It is also included some Open CV function overview, such as optical flow, 3D-2D points corresponding calculation and among others operations with rotation matrix. The end of this thesis provides outcomes evaluation and future work proposals.
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Font size adjustment based on distance detection
Brunclík, Robert ; Koťová, Markéta (referee) ; Janoušek, Oto (advisor)
The thesis deals with automatic control the font size by the distance from the reader. It includes theoretical acquaintance with the face detection and subsequent tracking of the detected area during the scene. Furthermore, there is a comparison of the tracking algorithms. Then the calculation of distance is decribed. It is based on the user’s calibration and based on the outcome occurs the font size is automatically corrected. There is also a description of a separate application Automatical controller of the text size, with the recommended settings of the program.
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Face Detection in Camera Image on a Mobile Phone
Tureček, Martin ; Láník, Aleš (referee) ; Herout, Adam (advisor)
This thesis deals with a face detection on mobile phones. It especially focuses on Windows Mobile platform. The introduction is therefore devoted to this operating system and alternatives of working with the camera. The next part of the text refers to general problems of the face detection in the image considering the weak performance of the target device. Another part of this thesis is a description of the acquisition of images from the camera using DirectShow multimedia framework and creation of a custom transformation filter for the face detection. Achieved results are summarized in the conclusion. It takes a form of tests examining different mobile devices. All difficulties arising during Windows Mobile developing are also mentioned.
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Masked face recognition
Kašpar, Jan ; Kříž, Petr (referee) ; Přinosil, Jiří (advisor)
This bachelor thesis focuses on the recognition of people with covered faces. The work describes four algorithms InsightFace, FaceNet, OpenFace, and face recognition. From these algorithms, the most suitable for recognizing people with a covered face is selected. Two databases of persons are created, and two models for the recognition of persons are trained; one is for the recognition of persons with a covered face and the other for non-covered persons. ROC curves are created for these models to determine the accuracy of the models. The created program is used to recognize people or to add them to the database created by SQLite.
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