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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Preventing Drowning Accidents Using Thermal Cameras
verfasst von : Soren Bonderup, Jonas Olsson, Morten Bonderup, Thomas B. Moeslund
Erschienen in: Advances in Visual Computing
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Abstract
Every year approximately 372 000 people die from unintentional drowning, causing it to be a top-3 cause to unintentional injury [1]. In Denmark 25% of drownings happen at harbor areas [2]. To address this problem thermal cameras have been placed strategically at a harbor. Using computer vision techniques an automatic surveillance system for predicting and detecting drowning accidents has been implemented. First a person detector has been implemented using simple human characteristics. The person is tracked using a Kalman Filter. Using the tracker as a prior, a fall prediction is determined. A fall detector is implemented using a virtual trip-wire in combination with an optical flow algorithm making the system able to detect 100% of all falls and only yielding a 0.08 false positive rate hourly. The entire system has been developed using 155 h of real life thermal video, hereof 56 h are manually annotated.