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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.
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Detection of Landscape in Images
Dufka, Zbyněk ; Křupka, Aleš (referee) ; Číka, Petr (advisor)
The target of this thesis is theoretical summary of methods, which are used for detection of objects in database of images. Next step is to develope own algorhytm for detection of landscape. Theoretical part describes methods Viola-Jones and HOG, which are used for detection of human faces and anomalies on radiographs. This analysis is concerned with segmentation method and algorhytm for data mining from images, which contain the landscape scenery. Appropriate method and its analysis could contribute to create and to implement into developement enviroment RapidMiner in the second part of thesis.
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Robotic Shopping Cart
Krzeminský, Juraj ; Kapinus, Michal (referee) ; Materna, Zdeněk (advisor)
This Bachelor thesis deals with design and implementation of control unit for robotic shopping cart. Its main task is to follow a chosen person through a mall and serve as bag carriage. The text describes basic principles of human detection and tracking in images and also the method of capturing them with RGB-D camera kinect. Rest of this text contain detailed description of created application and implementation of used methods and algorithms.
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Anatomy based landmark detection in brain CT scans
Krajčiová, Alexandra ; Harabiš, Vratislav (referee) ; Jakubíček, Roman (advisor)
Manual detection of anatomical landmarks from head CT (Computed Tomography) scans is time-consuming task prone to observer errors. In addition, the accuracy of the detection correlates with image quality. The aim of this work is to create an algorithm that will perform automatic detection of anatomical landmarks. These landmarks can be later used to form radiological lines, which finds its application in CT scanning. SVM (Support Vector Machines) and HOG (Histograms of Oriented Gradients) features was chosen for anatomical landmark detection. The achieved results, possibilities of further progress and improvement of detection are summarized in the conclusion.
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Efficiency of deep convolutional neural networks on an elementary classification task
Prax, Jan ; Dobrovský, Ladislav (referee) ; Škrabánek, Pavel (advisor)
In this thesis deep convolutional neural networks models and feature descriptor models are compared. Feature descriptors are paired with suitable chosen classifier. These models are a part of machine learning therefore machine learning types are described in this thesis. Further these chosen models are described, and their basics and problems are explained. Hardware and software used for tests is listed and then test results and results summary is listed. Then comparison based on the validation accuracy and training time of these said models is done.
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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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Face Features Extraction Methods
Adamček, Ľubomír ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
The face has been one of the most attractive available human biometries for a long time due to it's easy and convenient way to obtain it. Possibilities of it's utilization are broad - from security, through monitoring up to enternainment industry. This work presents the domain of face biometry and analyses 3 extraction methods of facial features - PCA, LBP and HOG. A part of this work is also an efficient implementation of these algorithms including GUI designed to experiment with this implementation and to evaluate its performance on a set of images capturing people in various conditions.
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Generating 3D Trees Based on Real Images
Kubiš, František ; Polok, Lukáš (referee) ; Szentandrási, István (advisor)
Master's thesis studies the possibilities of generating 3D trees using variety of methods including context-free grammars and L-systems. Master's thesis also includes chapter on evolutionary and genetic algorithms, which briefly summarize their function. In this project genetic algorithm which takes 2D image of tree and the beginning of its trunk is proposed. Based on this information it will generate 3D tree which is visually close to the original image. In addition to methods of generating trees, reader will get information about processing input image and designing test application.
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Estimate the Height of a Persons from the Video Data
Jelen, Vilém ; Orság, Filip (referee) ; Goldmann, Tomáš (advisor)
The aim of this bachelor thesis is to create an application that can detect pedestrians and make an estimate of their height from the video data. In the main part of the thesis I introduced security cameras and image processing methods suitable for detecting and classifying objects. Based on the comparison of these methods, I realized the pedestrian detection using Histograms of Oriented Gradients. As the input parameters of the proposed height estimation algorithm, I used the position and properties of the camera and reference objects or points.
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Smartphone Game Using Recognition of Face Features
Skoták, Jiří ; Szőke, Igor (referee) ; Herout, Adam (advisor)
This master's thesis focuses on smartphone game for iOS, which uses recognition of face features and other information, which can be obtained from a smartphone's camera and sensors. This work describes a few approaches for real-time face detection and then introduces and compares possibilities for such task on iOS. Moreover, the thesis contains a draft of the final game and its levels. The game showcases various technologies in its levels such as object detection, processing an image color and others. Finally, the thesis introduces the final form of the game that is released and available on the App Store.
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