@article{ref1,
title="A vision-based approach to early detection of drowning incidents in swimming pools",
journal="IEEE transactions on circuits and systems for video technology",
year="2004",
author="Lu, W. and Tan, Y.-p.",
volume="14",
number="2",
pages="159-178",
abstract="We present in this paper a vision-based approach to detection of drowning incidents in swimming pools at the earliest possible stage. The proposed approach consists of two main parts: a vision component which can reliably detect and track swimmers in spite of large scene variations of monitored pool areas, and an event-inference module which parses observation sequences of swimmer features for possible drowning behavioral signs. The vision component employs a model-based approach to represent and differentiate the background pool areas and foreground swimmers. The event-inference module is constructed based on a finite state machine, which integrates several reasoning rules formulated from universal motion characteristics of drowning swimmers. Possible drowning incidents are quickly detected using a sequential change detection algorithm. We have applied the proposed approach to a number of video clips of simulated drowning and obtained promising results as reported in this paper.<p /> <p>Language: en</p>",
language="en",
issn="1051-8215",
doi="10.1109/TCSVT.2003.821980",
url="http://dx.doi.org/10.1109/TCSVT.2003.821980"
}