Passive optical detection and classification of flying objects
but.event.date | 26.04.2022 | cs |
but.event.title | STUDENT EEICT 2022 | cs |
dc.contributor.author | Mošková, Andrea | |
dc.contributor.author | Vlachová Hutová, Eliška | |
dc.date.accessioned | 2022-12-06T13:21:57Z | |
dc.date.available | 2022-12-06T13:21:57Z | |
dc.date.issued | 2022 | cs |
dc.description.abstract | The article presents our solution for the classification of moving flying objects in a video sequence captured by a static camera. The tool uses the extraction of scale and rotation invariant SIFT features, which allow the multi-class SVM to classify the examined object into one of the considered classes: ‘bird’, ‘plane’ or ‘negative’. The most successful of our tested models achieved accuracy of over 90% and their recall and precision for each class reached values above 90%. | en |
dc.format | text | cs |
dc.format.extent | 67-70 | cs |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Proceedings II of the 28st Conference STUDENT EEICT 2022: Selected papers. s. 67-70. ISBN 978-80-214-6030-0 | cs |
dc.identifier.doi | 10.13164/eeict.2022.67 | |
dc.identifier.isbn | 978-80-214-6030-0 | |
dc.identifier.uri | http://hdl.handle.net/11012/208604 | |
dc.language.iso | en | cs |
dc.publisher | Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
dc.relation.ispartof | Proceedings II of the 28st Conference STUDENT EEICT 2022: Selected papers | en |
dc.relation.uri | https://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazeni | cs |
dc.rights | © Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
dc.rights.access | openAccess | en |
dc.subject | Object recognition, machine learning, SIFT, SVM, Matlab, motion detection | en |
dc.title | Passive optical detection and classification of flying objects | en |
dc.type.driver | conferenceObject | en |
dc.type.status | Peer-reviewed | en |
dc.type.version | publishedVersion | en |
eprints.affiliatedInstitution.department | Fakulta elektrotechniky a komunikačních technologií | cs |
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