Thesis Details

Rozpoznávání a klasifikace dopravních situací

Bachelor's Thesis Student: Zbořil Jiří Academic Year: 2021/2022 Supervisor: Smrž Pavel, doc. RNDr., Ph.D.
English title
Recognizing and Classification of Traffic Situations
Language
Czech
Abstract

The aim of this thesis is to identify and classify dangerous situations from surveillance cameras, monitoring traffic. An example of such situations is dangerous standing near by the road and car crash, on which this work focuses. The created system uses object detector, analyzing average images in given interval, K nearest neighbor and K Means algorithm and re-detection of enlarged local area in a frame to select anomaly candidates. Detected objects, that do not belong on the road are eliminated by attaching created road mask. At the very last phase, the interval, together with the classification is determined. Calculated F1 score is 0.645, S4 score 0.535 and precision of classification 80 %.

Keywords

anomaly detection, classification of situation, video analysis, object detection, backgroundmodeling, candidate selection

Department
Degree Programme
Files
Status
defended, grade D
Date
16 June 2022
Reviewer
Committee
Smrž Pavel, doc. RNDr., Ph.D. (DCGM FIT BUT), předseda
Burgetová Ivana, Ing., Ph.D. (DIFS FIT BUT), člen
Kreslíková Jitka, doc. RNDr., CSc. (DIFS FIT BUT), člen
Smrčka Aleš, Ing., Ph.D. (DITS FIT BUT), člen
Strnadel Josef, Ing., Ph.D. (DCSY FIT BUT), člen
Citation
ZBOŘIL, Jiří. Rozpoznávání a klasifikace dopravních situací. Brno, 2022. Bachelor's Thesis. Brno University of Technology, Faculty of Information Technology. 2022-06-16. Supervised by Smrž Pavel. Available from: https://www.fit.vut.cz/study/thesis/24437/
BibTeX
@bachelorsthesis{FITBT24437,
    author = "Ji\v{r}\'{i} Zbo\v{r}il",
    type = "Bachelor's thesis",
    title = "Rozpozn\'{a}v\'{a}n\'{i} a klasifikace dopravn\'{i}ch situac\'{i}",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2022,
    location = "Brno, CZ",
    language = "czech",
    url = "https://www.fit.vut.cz/study/thesis/24437/"
}
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