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Face detection in image
Kubalová, Eva ; Odstrčilík, Jan (referee) ; Mézl, Martin (advisor)
The bachelor thesis deals with the face detection in the picture, detection methods analysis and application of these methods in daily life. Chosen approach for detection, the segmentation based on the skin color, is realized and tested in MATLAB programming environment. In the thesis three different methods for face detection are described and samples of discovering and highlighting of the face characteristics, eyes and mouth, are presented. In addition, the evaluation of successfulness of particular methods is provided. The last part of the thesis contains simple user interface for the operation of the designed algorithms.
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Eye tracking
Magula, Filip ; Rajmic, Pavel (referee) ; Vlach, Jan (advisor)
This work deals with tracing the eyes in real-time video using infrared radiation treatment and detection of its rebound on pupils. It describes the human eye and its response to infrared radiation. It contains proposals for hardware and software solutions and the final realization of the basic options in Simulink, explains the selected methods of digital image processing and includes an assessment of the methods used in this work in conclusion.
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A System for Eye Movement Tracking
Urbanová, Lucie ; Marcoň, Petr (referee) ; Mikulka, Jan (advisor)
V této bakalářské práci jsou diskutovány možnosti a aplikace systému pro sledování pohybu očí, obsahující i aktuálně na trhu používané produkty. Práce následně uvádí řešení takového systému. Obsahuje návrh a realizaci držáku pro pevné uchycení kamery. Práce obsahuje i realizaci softvéru vytvořeného v C/C++ za využití Visual Studia a knihoven OpenCV. Tato aplikace sestává z procesů detekce očí, testování a vyhodnocení. Jako součást práce je provedeno a vyhodnoceno testování vytvořeného systému. Práce rovněž posuzuje vlastnosti systému a nabízí připadná rozšíření.
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Semiautomatic Collection of Large Database of Human Faces
Michalík, Marek ; Hradiš, Michal (referee) ; Herout, Adam (advisor)
The project is focused on methods of obtaining large number of images of human faces. Such database should then serve as a set of data for face detection and recognition by the means of supervised machine learning. The work deals with the basic principles of supervised machine learning and available data sets for this procedure. Project contains proposals of techniques and implementation of algorithms suitable for acquiring images from video and a concept of user interface for semi-automatic acceptation and annotation of located images.
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Face Anonymizer
Peša, Jan ; Juránek, Roman (referee) ; Láník, Aleš (advisor)
In this bachelor thesis you can find an overview of classification algorithms and their usage especially for searching image data and face detection. First part contains a brief introduction to a pattern recognition, a theoretical background of these algorithms and ways of training them. Other used components are also presented (e.g. Kalman filter or OpenCV library). Second part covers an implementation of the application which uses these technologies for searching, tracking and anononymization of human faces in a video stream.
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User Interface with Mobile Device and Camera
Rajca, Tomáš ; Zahrádka, Jiří (referee) ; Zemčík, Pavel (advisor)
The thesis describes the development of the user interface that uses the camera. By winking the left or right eye it is possible to emulate to two keys on the keyboard. For arranging the video it uses the library OpenCV. User interface is created by means of library Qt. This disertation includes an explanation of the basic propertis of the video, an explanation of principles of the video processing, overview of software applications, the software solution it selfs and implemenation of the application. In conclusion of this dissertaton resulsts are evaulated and potential further development is described.
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A System For Eye Movement Tracking
Urbanová, Lucie
The goal of this project is to design the real-time eye movement tracking system, realise it and perform measuring on several subjects to verify its functionality and precision. The eye movement tracking system consists of a camera attached to the camera holder mounted on subject´s head. The camera captures the eye of the subject and the measuring software detects the iris. The software then calculates the location the subject is looking at using the input video of the eye, the calibration results and the head movement measuring device.
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