Experimental Solution for Estimating Pedestrian Locations from UAV Imagery
This research describes an experimental solution used for estimating the positions of pedestrians from video recordings. Additionally, clustering algorithms were utilized to interpret the data. The system employs the You Only Look Once (YOLO) algorithm for object detection. The detection algorithm i...
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| Published in | Applied sciences Vol. 12; no. 19; p. 9485 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
MDPI AG
01.10.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2076-3417 2076-3417 |
| DOI | 10.3390/app12199485 |
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| Abstract | This research describes an experimental solution used for estimating the positions of pedestrians from video recordings. Additionally, clustering algorithms were utilized to interpret the data. The system employs the You Only Look Once (YOLO) algorithm for object detection. The detection algorithm is applied to video recordings provided by an unmanned aerial vehicle (UAV). An experimental method for calculating the pedestrian’s geolocation is proposed. The output of the calculation, i.e., the data file, can be visualized on a map and analyzed using cluster analyses, including K-means, DBSCAN, and OPTICS algorithms. The experimental software solution can be deployed on a UAV or other computing devices. Further testing was performed to evaluate the suitability of the selected algorithms and to identify optimal use cases. This solution can successfully detect groups of pedestrians from video recordings and it provides tools for subsequent cluster analyses. |
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| AbstractList | This research describes an experimental solution used for estimating the positions of pedestrians from video recordings. Additionally, clustering algorithms were utilized to interpret the data. The system employs the You Only Look Once (YOLO) algorithm for object detection. The detection algorithm is applied to video recordings provided by an unmanned aerial vehicle (UAV). An experimental method for calculating the pedestrian’s geolocation is proposed. The output of the calculation, i.e., the data file, can be visualized on a map and analyzed using cluster analyses, including K-means, DBSCAN, and OPTICS algorithms. The experimental software solution can be deployed on a UAV or other computing devices. Further testing was performed to evaluate the suitability of the selected algorithms and to identify optimal use cases. This solution can successfully detect groups of pedestrians from video recordings and it provides tools for subsequent cluster analyses. |
| Author | Michalko, Miroslav Gera, Marek Jakab, František Kainz, Ondrej |
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| Cites_doi | 10.1109/ICCV.2017.322 10.3390/drones6050109 10.1007/s42979-020-00125-y 10.3390/rs14040874 10.3390/s21062180 10.3390/rs14020295 10.3390/app12073627 10.3390/drones5030058 10.1109/CVPR.2014.81 10.1109/TMM.2020.3019688 10.3390/ijgi10050284 10.3390/aerospace9040198 10.1007/s12652-021-03570-6 10.1007/978-3-319-46448-0_2 10.3390/s22093502 10.1109/CVPR.2016.91 10.3390/s20247299 10.3390/s22072455 10.3390/electronics11071151 10.3390/s18072244 10.3390/s22020464 10.3390/drones6030076 10.3390/rs13163095 10.3390/rs14061434 10.3390/rs14133143 |
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| Title | Experimental Solution for Estimating Pedestrian Locations from UAV Imagery |
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