|
|
Object Detection Using Kinect
Švec, Ján ; Zahrádka, Jiří (referee) ; Španěl, Michal (advisor)
This bachelor's thesis deals with the object detection using Kinect. Kinect is a motion sensing input device by Microsoft company for the Xbox 360 video game console. The objective of this work was to evaluate the existing approaches and practices for the detection not only using the image from the camera but also depth map (RGB-D sensor). The work deals in details with RoboEarth tool, its installation, settings, creation of 3D model and the detection. Performance of the RoboEarth tool was in the work investigated experimentally and also evaluated.
|
|
|
Automatic Content-Based Image Categorization
Němec, Ladislav ; Španěl, Michal (referee) ; Veľas, Martin (advisor)
This thesis deals with automatic content-based image classification. The main goal of this work is implementation of application which is able to perform this task automatically. The solution consists of variable system using local image features extraction and visual vocabulary built by k-means method. Bag Of Words representation is used as a global feature describing each image. Support Vector Machines - the final component of this system - perform the classification based on this representation. In the last chapter, the results of this experimental system are presented.
|
|
|
Weapon Detection in an Image
Debnár, Pavol ; Drahanský, Martin (referee) ; Dvořák, Michal (advisor)
This thesis is focused on the topic of firearms detection in images. In the theoretic section, the explanation of the term firearm is covered, along with the definition of the most prevalent firearm categories. Then the concept of image noise and the ways it can hinder image detection is covered, along with ways of reducing it. Next, algorithms of image detection are introduced - first those which operate on the basis of neural nets - such as Convolutional Neural Nets and Single Shot Multibox Detection. The next section discusses classic algorithms of object detection such as HOG+SVM and SURF. After that, information on the used libraries and software is provided. The experimental part covers the designed algorithm and database. For detection, the HOG+SVM, SURF and SSD algorithms were used. All the algorithms are tested on the database and, if possible, on video. A final evaluation is provided, along with possible future development options.
|
|
|
Augmented Reality for Flight Simulator Based on Background Keying
Vahalík, Tomáš ; Maršík, Lukáš (referee) ; Beran, Vítězslav (advisor)
This thesis deals with a design of a method for determination of the view direction within a scene and an exact registration of a camera picture with a model of the scene for background keying. The methods for an image description by interest points are parts of this thesis, especially the methods SURF, FAST and Brief. A demo application, which tests are described here as well, presents a correspondence determination between an input image from a camera and a created model of the scene. The main use of this work rests in augmented reality together with determination of the user's view direction.
|
|
|
Processing of Video Records
Čerešňák, Michal ; Drahanský, Martin (referee) ; Zemčík, Pavel (advisor)
V této práci je prezentován systém pro zpracování videa se zaměřením na detekci a rozeznávání obličejů. Systém zpracovává video stream z kamery v reálném čase. K detekci obličejů využívá ViolaJones detektor. Pro rozeznávání obličejů je použita metoda SURF. Systém je implementován v jazyce C# a využívá knihovnu OpenCV a Emgu CV wrapper.
|
|
|
Object tracking in videosequence
Nešpor, Zdeněk ; Zukal, Martin (referee) ; Číka, Petr (advisor)
This thesis deals with tracking a predefined object in the movie. After a brief introduction describes the procedure suitable for the detection of an object in a video sequence, where the methods are also discussed in detail. There is dealt with issues of image preprocessing, image segmentation and object detection in the image. The main emphasis is laid on using detectors of interest points and descriptors of areas - SURF and SIFT. The second part deals with the practical implementation of a program suitable to monitor predefined object in the movie. First are analyzed libraries suitable for object tracking in a video sequence in an environment of Java, followed by a detailed description of the selected library OpenCV along with wrapper JavaCV. Further described is own application in terms of control and functionality are described key method. Outputs along with discussion and evaluation are presented at the end of work.
|
|
|
Automatic Photography Categorization
Veľas, Martin ; Řezníček, Ivo (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to experiment with advanced techniques of image represenatation and to create a classifier which is able to process large image dataset with sufficient accuracy and computation speed. A traditional solution based on using visual codebooks is enhanced by computing color features, soft assignment of visual words to extracted feature vectors, usage of image segmentation in process of visual codebook creation and dividing picture into cells. These cells are processed separately. Linear SVM classifier with explicit data embeding is used for its efficiency. Finally, results of experiments with above mentioned techniques of the image categorization are discussed.
|
|
|
Embedded display recognition
Novotný, Václav ; Janáková, Ilona (referee) ; Honec, Peter (advisor)
This master thesis deals with usage of machine learning methods in computer vision for classification of unknown images. The first part contains research of available machine learning methods, their limitations and also their suitability for this task. The second part describes the processes of creating training and testing gallery. In the practical part, the solution for the problem is proposed and later realised and implemented. Proper testing and evaluation of resulting system is conducted.
|
|
|
Image objects detection based on the feature points matching
Trávníček, Vojtěch ; Macíček, Ondřej (referee) ; Harabiš, Vratislav (advisor)
This paper is concerned in branch of computer vision. Methods for extracting feature points are presented as tools for image comparison and finding objects in images. Four methods are metioned which are compared with respect to their effectiveness and utilization. Algorythms SIFT and SURF are described as a state-of-the-arts. This paper also mentions methods for describing feature points and their comparison. Testing images are inserted as a tool for first testing of implemented algorythm. Finally, the implemented method SURF is described and tested with respect to several most relevant parameters.
|
|
|
Eye Tracking in User Interfaces
Jurzykowski, Michal ; Beran, Vítězslav (referee) ; Zemčík, Pavel (advisor)
Tato diplomová práce byla vytvořena během studijního pobytu na Uviversity of Estern Finland, Joensuu, Finsko. Tato diplomová práce se zabývá využitím technologie sledování pohledu neboli také sledování pohybu očí (Eye-Tracking) pro interakci člověk-počítač (Human-Computer Interaction (HCI)). Navržený a realizovaný systém mapuje pozici bodu pohledu/zájmu (the point of gaze), která odpovídá souřadnicím v souřadnicovém systému kamery scény do souřadnicového systému displeje. Zároveň tento systém kompenzuje pohyby uživatele a tím odstraňuje jeden z hlavních problémů využití sledování pohledu v HCI. Toho je dosaženo díky stanovení transformace mezi projektivním prostorem scény a projektivním prostorem displeje. Za použití význačných bodů (interesting points), které jsou nalezeny a popsány pomocí metody SURF, vyhledání a spárování korespondujících bodů a vypočítání homografie. Systém byl testován s využitím testovacích bodů, které byly rozložené po celé ploše displeje.
|
guest ::
