Detection of early dangerous state in deep water of indoor swimming pool based on surveillance video

This paper presents a method for early detection of dangerous condition in the deep-water zone of swimming pool based on video surveillance. We propose feature extraction, feature expression and assessment criteria, including a method for evaluating normal swimming speed based on the time series of...

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Published in:Signal, image and video processing image and video processing, 2022-02, Vol.16 (1), p.29-37
Main Authors: Wang, Fan, Ai, Yibo, Zhang, Weidong
Format: Article
Language:English
Subjects:
Computer Imaging
Computer Science
Deep water
Feature extraction
Image Processing and Computer Vision
Multimedia Information Systems
Original Paper
Pattern Recognition and Graphics
Signal,Image and Speech Processing
Surveillance
Swimming
Swimming pools
Vision
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cited_by cdi_FETCH-LOGICAL-c249t-b02a1718de51c3362235e73cff55136afce2d9347c7a71b61b56b200ffb65583
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creator Wang, Fan
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Zhang, Weidong
description This paper presents a method for early detection of dangerous condition in the deep-water zone of swimming pool based on video surveillance. We propose feature extraction, feature expression and assessment criteria, including a method for evaluating normal swimming speed based on the time series of swimmers, a method for assessing an upright state that is not limited by the camera angle, and the rules for assessing dangerous state. We have collected real-life data from the swimming pool and conducted related experiments. Our method can easily and efficiently detect the swimmer who is in danger at an early stage and provide necessary rescue reminders to lifeguards.
doi_str_mv 10.1007/s11760-021-01953-y
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subjects Computer Imaging
Computer Science
Deep water
Feature extraction
Image Processing and Computer Vision
Multimedia Information Systems
Original Paper
Pattern Recognition and Graphics
Signal,Image and Speech Processing
Surveillance
Swimming
Swimming pools
Vision
title Detection of early dangerous state in deep water of indoor swimming pool based on surveillance video
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