Deep Learning Used to Recognition Swimmers Drowning

Abstract

Many people believe that when drowning occurs, there will be calls for help. In fact, people who are drowning do not get too many splashes or cry for help. They only try to get themselves out of the water by treading on the water. The drowning condition may cause serious brain damage, so it is extremely important to shorten the time it takes to detect the occurrence of drowning and rescue.This paper proposes using computer image processing technology to introduce artificial intelligence motion technology, mounting the camera on the bottom of the swimming pool, and use OpenPose to mark the image joint point features, and input the captured joint point features into the recursive neural network to determine whether the swimmer is drowning. The final training result is about 89.4% accurate, so it can be used to assist on-site lifeguards to detect swimmers who may be drowning, and to reduce incidents that cannot be detected immediately