DEWS: A live visual surveillance system for early drowning detection at pool

How Lung Eng, Kar Ann Toh, Wei Yun Yau, Junxian Wang

Research output: Contribution to journalArticlepeer-review

45 Citations (Scopus)

Abstract

A real-time vision system operating at an outdoor swimming pool is presented in this paper. The system is designed to automatically recognize different swimming activities and to detect occurrence of early drowning incidents. We have named this system the Drowning Early Warning System (DEWS). One key challenge we faced in the problem is the relatively high level of noise in the steps of foreground detection and behavior recognition. Therefore, a set of methods in the fields of background subtraction, denoising, data fusion and blob splitting are proposed, which have been motivated by characteristics of aquatic background and crowded scenario at the pool. In the step to detect an early drowning incident, visual indicators of distress and drowning are incorporated through a set of foreground descriptors. A module comprising data fusion and hidden Markov modeling is developed to learn unique traits of different swimming behaviors, in particular, those early drowning events. The experiment of this work reports realistic on-site evaluations performed. Examples of interesting behaviors, i.e., distress, drowning, treading and numerous swimming styles, are simulated and collected. Experimental results show that we have established a prototype system which is robust and beyond the stage of proof-of-concept.

Original languageEnglish
Article number4399966
Pages (from-to)196-210
Number of pages15
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume18
Issue number2
DOIs
Publication statusPublished - 2008 Feb

Bibliographical note

Funding Information:
Manuscript received October 20, 2006; revised February 8, 2007. This work was supported by the Enterprise Challenge Unit, Singapore’s Prime Minister’s Office and the Singapore Sports Council. This paper was recommended by Associate Editor D. S. Turaga. H.-L. Eng is with the Institute for Infocomm Research, 119613 Singapore (e-mail: hleng@i2r.a-star.edu.sg). K.-A. Toh is with the Biometrics Engineering Research Center, School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, Korea. W.-Y. Yau is with the School of Electrical and Electronic Engineering,Nanyang Technological University, 639789 Singapore, and also with the Institute for Infocomm Research, 119613 Singapore. J. Wang is with the Computer Science and Engineering Department, University of Nevada, Reno, NV 89557 USA. Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TCSVT.2007.913960

All Science Journal Classification (ASJC) codes

  • Media Technology
  • Electrical and Electronic Engineering

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