Szczegóły publikacji
Opis bibliograficzny
Dangerous tool detection for CCTV systems / Paweł Donath, Michał GREGA, Piotr GUZIK, Jakub Król, Andrzej MATIOLAŃSKI, Krzysztof RUSEK // W: Multimedia Communications, Services and Security : 10th international conference, MCSS 2020 : Kraków, Poland, October 8–9, 2020 : proceedings. — Cham : Springer Nature Switzerland, cop. 2020. — (Communications in Computer and Information Science ; ISSN 1865-0929 ; vol. 1284). — ISBN: 978-3-030-58999-8; e-ISBN: 978-3-030-59000-0. — S. 238–251. — Bibliogr. s. 250–251, Abstr. — Publikacja dostępna online od: 2020-09-24
Autorzy (6)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 130813 |
|---|---|
| Data dodania do BaDAP | 2020-11-03 |
| DOI | 10.1007/978-3-030-59000-0_18 |
| Rok publikacji | 2020 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Czasopismo/seria | Communications in Computer and Information Science |
Abstract
In this paper we present our work towards an effective solution for detection of dangerous objects, such as firearms or knives in a Closed Circuit Television System. We have gathered a large, manually annotated dataset of recordings supplemented by our original artificial sample generation method. We have used this dataset for training of a convolutional neural network. We present our approach and training results. We have also implemented and present software architecture that implements the neural network. We have shown, that the convolutional neural networks are well suited even for such complex object detection task, when provided with enough training samples.
