Thesis Details
Rozpoznávání a klasifikace dopravních situací
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 %.
anomaly detection, classification of situation, video analysis, object detection, backgroundmodeling, candidate selection
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
@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/"
}