Thesis Details

Sledování pohyblivých objektů ve videu

Bachelor's Thesis Student: Folenta Ján Academic Year: 2019/2020 Supervisor: Herout Adam, prof. Ing., Ph.D.
Language
Slovak
Abstract

This bachelor thesis deals with the issue of detection, tracking and counting vehicles in different directions in video. To deal with this problem, modern techniques of object detection and tracking using convolutional neural networks are used. The goal of this work is to achieve highest possible accuracy of vehicle counting while maintaining the processing of video recordings in real-time. The problems of the implemented method for detection and tracking are solved by analyzing and working with the trajectories of vehicles. With accuracy of 90,94% and total score of 0,8829, this work participated in AI City Challenge 2020, where it placed 6th.

Keywords

object detection, object tracking, CNN, YOLOv3, Deep SORT, AI City Challenge, trajectories

Department
Department of Computer Graphics and Multimedia FIT BUT
Degree Programme
Information Technology
Files
Status
defended, grade B
Date
9 July 2020
Reviewer
Bartl Vojtěch, Ing.
Committee
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT), předseda
Bidlo Michal, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Čadík Martin, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Grégr Matěj, Ing., Ph.D. (DIFS FIT BUT), člen
Kočí Radek, Ing., Ph.D. (DITS FIT BUT), člen
Citation
FOLENTA, Ján. Sledování pohyblivých objektů ve videu. Brno, 2020. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2020-07-09. Supervised by Herout Adam. Available from: https://www.fit.vut.cz/study/thesis/20515/
BibTeX 
@bachelorsthesis{FITBT20515,
    author = "J\'{a}n Folenta",
    type = "Bachelor's thesis",
    title = "Sledov\'{a}n\'{i} pohybliv\'{y}ch objekt\r{u} ve videu",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2020,
    location = "Brno, CZ",
    language = "slovak",
    url = "https://www.fit.vut.cz/study/thesis/20515/"
}

Theses

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