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Person's identification by means of bipedal locomotion
Krzyžanek, Jakub ; Richter, Miloslav (referee) ; Horák, Karel (advisor)
The aim of this thesis is to recognize a walking person in a sequence of images by defining his or her reference points to compare the course of their movement and then to identify the scanned person. Methods „k-means“ and „mean shift“ are used to obtain the silhouette of the person. However “environment model estimation” method is used here before those mentioned above. It is a type of a difference method and it helps to specify the scanning area and shortens the time of segmentation. During the search for the reference points the thesis focuses on three areas: the centre of the head and both ankle joints. Those points are later determined on the previous image sequence and compared with the real locations of the centre of the head and ankle joints marked by the user. The thesis also focuses on comparing the movement courses of those points and tries to identify the people whose walks are being scanned. Problematic situations which occurred during the whole process are analyzed in the end. The result of the thesis is an algorithm which can locate a moving person in an image sequence (video) and determine the reference points (centre of the head and ankles) to compare them and identify the scanned person.
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Line tracking for delivery robot
Juhas, Miroslav ; Horák, Karel (referee) ; Janáková, Ilona (advisor)
This thesis describes basics of methods and algorithms used in computer vision and application of them at a simple practical problem – line-tracking for delivery robot. The first part of this thesis contains basic theoretical knowledge of computer vision, which is important for understanding the problem. It is an introduction to problems of computer vision. The second part of thesis describes solving of particular steps, which are image preprocessing, segmentation, trajectory detection and algorithms for direction control. It contains outcomes of particular steps and selection of methods acceptable for solving the problem. There are presented experiences with tests of algorithms on the UTAR platform in context of this work. The last part of thesis is evaluating results taken during work.
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Effect of vibration on image quality of the electron microscope
Šafář, Pavel ; Horák, Karel (referee) ; Havránek, Zdeněk (advisor)
My thesis focuses on one the parasitic factors influencing an electron microscope during recording - i.e. the vibrations. Their impact on the quality of the shots is crucial and it is thus desirable to discover the origin of the vibrations and the way they are transmitted on the device and also to strive to eliminate this phenomen as much as possible. Measurements to estimate the source of vibration on the device as well as in its surrounding are a part of my work.
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Unary Classification of Image Data
Beneš, Jiří ; Petyovský, Petr (referee) ; Horák, Karel (advisor)
The work deals with an introduction to classification algorithms. It then divides classifiers into unary, binary and multi-class and describes the different types of classifiers. The work compares individual classifiers and their areas of use. For unary classifiers, practical examples and a list of used architectures are given in the work. The work contains a chapter focused on the comparison of the effects of hyper parameters on the quality of unary classification for individual architectures. Part of the submission is a practical example of reimplementation of the unary classifier.
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Image processing using Android - LPR with external database
Molčány, Peter ; Horák, Karel (referee) ; Honec, Peter (advisor)
The aim of this Master's thesis is designing and developing Android application for automatic number plate recognition with external database lookup. In the introduction we discuss possibilities of number plate recognition in general. Android platform fundamentals, necessary developer tools and multi-platform image processing library OpenCV are described in the second section. In the third section different database types and synchronization methods are introduced. In the fourth section we describe basics of image processing and different algorithms necessary for recognition. Application requirements, involving scene and hardware requirements are defined in the fifth section. In the sixth section application development and algorithm implementation is described. In the seventh section we evalute the results of the detection. In the last section results are summarized and goals are set for further improvement.
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Deep Learning Algorithms on Embedded Devices
Hadzima, Jaroslav ; Boštík, Ondřej (referee) ; Horák, Karel (advisor)
Táto práca popisuje v súčastnosti široko používané architektúry a modely pre Hlboké Učenie, riešiace úlohu detekcie a klasifikácie objektov vo videu. Dôraz tu bude kladený na ich použiteľnosť na vstavaných zariadeniach. Postupne preberieme kroky a odvôvodňovanie pri výbere najlepšieho vstavaného systému pre našu aplikáciu. Ukážková aplikáci pozostáva hlavne z detekcie vozidiel a detekcie voľných parkovacích miest s využitím algoritmov Hlbokého Učenia. Táto aplikácia umožňuje monitorovať počet vozidiel, nachádzajúcich sa na parkovisku a zároveň rozhodnúť, či sa nachádzajú na prakovacom mieste alebo nie. Následne tu budú prebrané kroky nutné ku konfigurácii zariadenia s dôrazom na optimalizáciu hardvéru pre dosiahnutie čo najväčšej rýchlosti. V ďaľšej časti bude poskytnuté porovnanie vybraných modelov, ktoré budú porovnávané hlavne v kategóriách ako rýchlosť alebo F1 skóre. Najlepší kandidát bude použitý na riešenie našej aplikácie a následné testovanie jej vlastností s názvom Inteligentné parkovisko.
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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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Moving object tracking
Sehnoutka, Martin ; Horák, Karel (referee) ; Richter, Miloslav (advisor)
This thesis deals with application of computer vision for purposes of object tracking in a video record. In first part of this document, algorithms of computer vision are described theoretically. Next part contains design of map of movement in a scene. All these procedures were used during implementation of program for tracking of moving objects. Discussion of program functionality is in the last chapter.
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Projector camera cooperation
Walter, Viktor ; Horák, Karel (referee) ; Richter, Miloslav (advisor)
The focus of this thesis is the cooperation of cameras and projectors in projection of data into a scene. It describes the means and theory necessary to achieve such cooperation, and suggests tasks for demonstration. A part of this project is also a program capable of using a camera and a projector to obtain necessary parameters of these devices. The program can demonstrate the quality of this calibration by projecting a pattern onto an object according to its current pose, as well as reconstruct the shape of an object with structured light. The thesis also describes some challenges and observations from development and testing of the program.
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