Szczegóły publikacji
Opis bibliograficzny
New thermal automotive dataset for object detection / Tomasz Balon, Mateusz KNAPIK, Bogusław CYGANEK // W: FedCSIS 2022 [Dokument elektroniczny] : position papers of the 17th conference on Computer Science and Intelligence Systems : September 4–7, 2022, Sofia, Bulgaria / eds. Maria Ganzha, Leszek Maciaszek, Marcin Paprzycki, Dominik Ślęzak. — Wersja do Windows. — Dane tekstowe. — Warszawa : Polskie Towarzystwo Informatyczne, cop. 2022. — (Annals of Computer Science and Information Systems ; ISSN 2300-5963 ; vol. 31). — Dod. ISBN USB 978-83-965897-3-6. — e-ISBN: 978-83-965897-2-9. — S. 43–48. — Wymagania systemowe: Adobe Reader. — Tryb dostępu: https://annals-csis.org/Volume_31/pliks/position.pdf [2022-10-06]. — Bibliogr. s. 48, Abstr. — W części: 4th International Workshop on Artificial Intelligence in Machine Vision and Graphics. — M. Knapik - dod. afiliacja: MyLED Inc., Kraków
Autorzy (3)
Dane bibliometryczne
| ID BaDAP | 142905 |
|---|---|
| Data dodania do BaDAP | 2022-10-27 |
| DOI | 10.15439/2022F283 |
| Rok publikacji | 2022 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Konferencja | 2022 17th Conference on Computer Science and Intelligence Systems |
| Czasopismo/seria | Annals of Computer Science and Information Systems |
Abstract
Although there are many efficient deep learningmethods, object detection and classification in visible spectrum have many limitations especially in case of poor light conditions. To fill this gap, we created a novel thermal video database containing few thousands of frames with annotated objects acquired in far infrared thermal spectrum. Thanks to this we were able to show its usability in the traffic object recognition based on the YOLOv5 network, properly trained to gain maximal performance on thermal images, which contain many small objects and are characteristic of different properties than the visible spectrum counterparts. The proposed thermal database, as well as the fully trained model are main contributions of this paper. These are made available free for other researchers. Additionally, based on the highly efficient car detector we show its application in the car speed measurement based exclusively on thermal images. The proposed system can be also used in the Advanced DriverAssistance Systems (ADAS), and help autonomous driving.