Thesis Details

Detektor ohně ve videu

Master's Thesis Student: Poledník Tomáš Academic Year: 2014/2015 Supervisor: Herout Adam, prof. Ing., Ph.D.
English title
Detection of Fire in Video
Language
Czech
Abstract
{This thesis deals with fire detection in video by colour analysis and machine learning, specifically deep convolutional neural networks, using Caffe framework. The aim is to create a vast set of data that could be used as the base element of machine learning detection and create a detector usable in real application. For the purposes of the project a set of tools for fire sequences creation, their segmentation and automatic labeling is proposed and created together with a large test set of short sequences with artificial modelled fire.
Keywords

Fire detection, image processing, video sequence, machine learning by deep convolutional neural networks, computer vision, Caffe, fire modelling, fire scene compositing

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology, Field of Study Intelligent Systems
Files
Status
defended, grade B
Date
24 June 2015
Reviewer
Hradiš Michal, Ing., Ph.D.
Committee
Zbořil František V., doc. Ing., CSc. (DITS FIT BUT), předseda
Bidlo Michal, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Češka Milan, prof. RNDr., CSc. (DITS FIT BUT), člen
Lucká Mária, prof. RNDr., Ph.D. (FIIT STU), člen
Očenášek Pavel, Mgr. Ing., Ph.D. (DIFS FIT BUT), člen
Švéda Miroslav, prof. Ing., CSc. (DIFS FIT BUT), člen
Citation
POLEDNÍK, Tomáš. Detektor ohně ve videu. Brno, 2015. Master's Thesis. Brno University of Technology, Faculty of Information Technology. 2015-06-24. Supervised by Herout Adam. Available from: https://www.fit.vut.cz/study/thesis/17817/
BibTeX 
@mastersthesis{FITMT17817,
    author = "Tom\'{a}\v{s} Poledn\'{i}k",
    type = "Master's thesis",
    title = "Detektor ohn\v{e} ve videu",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2015,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/17817/"
}

Theses

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