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Open AccessArticle

Visual-Based Person Detection for Search-and-Rescue with UAS: Humans vs. Machine Learning Algorithm

1
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, 21000 Split, Croatia
2
Faculty of Mechanical Engineering, Computing and Electrical Engineering, University of Mostar, 88000 Mostar, Bosnia and Herzegovina
3
Faculty of Science and Education, University of Mostar, 88000 Mostar, Bosnia and Herzegovina
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(20), 3295; https://doi.org/10.3390/rs12203295
Received: 31 August 2020 / Revised: 30 September 2020 / Accepted: 8 October 2020 / Published: 10 October 2020
Unmanned Aircraft Systems (UASs) have been recognized as an important resource in search-and-rescue (SAR) missions and, as such, have been used by the Croatian Mountain Search and Rescue (CMRS) service for over seven years. The UAS scans and photographs the terrain. The high-resolution images are afterwards analyzed by SAR members to detect missing persons or to find some usable trace. It is a drawn out, tiresome process prone to human error. To facilitate and speed up mission image processing and increase detection accuracy, we have developed several image-processing algorithms. The latest are convolutional neural network (CNN)-based. CNNs were trained on a specially developed image database, named HERIDAL. Although these algorithms achieve excellent recall, the efficiency of the algorithm in actual SAR missions and its comparison with expert detection must be investigated. A series of mission simulations are planned and recorded for this purpose. They are processed and labelled by a developed algorithm. A web application was developed by which experts analyzed raw and processed mission images. The algorithm achieved better recall compared to an expert, but the experts achieved better accuracy when they analyzed images that were already processed and labelled. View Full-Text
Keywords: search and rescue (SAR); Unmanned Aircraft System (UAS); Deep CNN; aerial image processing; CNN; expert to CNN comparison search and rescue (SAR); Unmanned Aircraft System (UAS); Deep CNN; aerial image processing; CNN; expert to CNN comparison
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MDPI and ACS Style

Gotovac, S.; Zelenika, D.; Marušić, Ž.; Božić-Štulić, D. Visual-Based Person Detection for Search-and-Rescue with UAS: Humans vs. Machine Learning Algorithm. Remote Sens. 2020, 12, 3295.

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