Passive optical detection and classification of flying objects
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Date
2022
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Mark
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Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
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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%.
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Citation
Proceedings II of the 28st Conference STUDENT EEICT 2022: Selected papers. s. 67-70. ISBN 978-80-214-6030-0
https://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazeni
https://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazeni
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Peer-reviewed
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en
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© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií