주․야간 상시 수상안전 감시를 위한 무인화 모빌리티 기반의 익수자 탐지 및 위치추정 모델
Drowning Detection and Localization Using Unmanned Mobile Systems for 24/7 Water Safety Surveillance
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In this paper, a water rescue mission system was developed for water safety management areas by utilizing unmanned mobi- lity(drone systems) and AI-based visual recognition technology to enable automatic detection and localization of drowning persons, allowing timely response within the golden time. First, we detected suspected human subjects in daytime and nighttime videos, then estimated human skeleton-based poses to extract human features and patterns using LSTM models. After detecting the drowning person, we proposed an algorithm to obtain accurate GPS location information of the drowning person for rescue activities. In our experimental results, the accuracy of the Drown detection rate is 80.1% as F1-Score, and the average error of position estimation is about 0.29 meters.
Abstract
In this paper, a water rescue mission system was developed for water safety management areas by utilizing unmanned mobi- lity(drone systems) and AI-based visual recognition technology to enable automatic detection and localization of drowning persons, allowing timely response within the golden time. First, we detected suspected human subjects in daytime and nighttime videos, then estimated human skeleton-based poses to extract human features and patterns using LSTM models. After detecting the drowning person, we proposed an algorithm to obtain accurate GPS location information of the drowning person for rescue activities. In our experimental results, the accuracy of the Drown detection rate is 80.1% as F1-Score, and the average error of position estimation is about 0.29 meters.