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An automatic drowning detection surveillance system for challenging outdoor pool environments
Eng, H.-L.; Toh, K.-A.; Kam, A.H.; Wang, J.; Yau, W.-Y.;
Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on
13-16 Oct. 2003
Page(s):532
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539 vol.1
Abstract:
Automatically understanding events happening at a site is the ultimate goal of visual surveillance system. We investigate the challenges faced by automated surveillance systems operating in hostile conditions and demonstrate 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 modelling 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.
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