Return to search

Detekce pohybujících se objektů ve videu s využitím neuronových sítí / Object detection in video using neural networks

This diploma thesis deals with the detection of moving objects in a video recording using neural networks. The aim of the thesis was to detect road users in video recordings. Pre-trained YOLOv5 object detection model was used for a practical part of the thesis. As part of the solution, an own dataset of traffic road video recordings was created and annotated with following classes: a car, a bus, a van, a motorcycle, a truck and a trailer truck. Final version of this dataset comprise 5404 frames and 6467 annotated objects in total. After training, the YOLOv5 model achieved 0.995 mAP, 0.995 precision and 0.986 recall on the dataset. All steps leading to the final form of the dataset are described in the conclusion chapter.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:442377
Date January 2021
CreatorsMikulský, Petr
ContributorsSikora, Pavel, Myška, Vojtěch
PublisherVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

Page generated in 0.0018 seconds