An automatic drowning detection surveillance system for challenging outdoor pool environments

How Lung Eng, Kar Ann Toh, Alvin H. Kam, Junxian Wang, Wei Yun Yau

Research output: Contribution to conferencePaper

41 Citations (Scopus)

Abstract

Automatically understanding events happening at a site is the ultimate goal of visual surveillance system. This paper investigates the challenges faced by automated surveillance systems operating in hostile conditions and demonstrates the developed algorithms via a system that detects water crises within highly dynamic aquatic environments. An efficient segmentation algorithm based on robust block-based background modeling and thresholding-with-hysteresis methodology enables swimmers to be reliably detected amid reflections, ripples, splashes and rapid lighting changes. Partial occlusions are resolved using a Markov Random Field framework that enhances the tracking capability of the system. Visual indicators of water crises are identified based on professional knowledge of water crises detection, based on which a set of swimmer descriptors has been defined. Through seamlessly fusing the extracted swimmer descriptors based on a novel functional link network, the system achieves promising results for water crises detection. The developed algorithms have been incorporated into a live system with robust performance for different hostile environments faced by an outdoor swimming pool.

Original languageEnglish
Pages532-539
Number of pages8
Publication statusPublished - 2003 Dec 2
EventProceedings: Ninth IEEE International Conference on Computer Vision - Nice, France
Duration: 2003 Oct 132003 Oct 16

Other

OtherProceedings: Ninth IEEE International Conference on Computer Vision
CountryFrance
CityNice
Period03/10/1303/10/16

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All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

Cite this

Eng, H. L., Toh, K. A., Kam, A. H., Wang, J., & Yau, W. Y. (2003). An automatic drowning detection surveillance system for challenging outdoor pool environments. 532-539. Paper presented at Proceedings: Ninth IEEE International Conference on Computer Vision, Nice, France.