Original title: Passive optical detection and classification of flying objects
Authors: Mošková, Andrea ; Vlachová Hutová, Eliška
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
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%.
Keywords: Object recognition, machine learning, SIFT, SVM, Matlab, motion detection
Host item entry: Proceedings II of the 28st Conference STUDENT EEICT 2022: Selected papers, ISBN 978-80-214-6030-0

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/208604

Permalink: http://www.nusl.cz/ntk/nusl-511873


The record appears in these collections:
Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers