An automatic drowning detection surveillance system for challenging outdoor pool environments

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-withhysteresis 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 prom...

• Type: Conference
• Year: 2003
• Where: ICCV
• Authors: How-Lung Eng, Kar-Ann Toh, Alvin Harvey Kam, Junxian Wang, Wei-Yun Yau
• Keywords: Computer Vision, ICCV 2003, Surveillance Systems, Water Crises, Water Crises Detection