Abstract: Fire-related incidents account for extensive loss of life and
material damage. Quick and reliable detection of occurring fires has high
real world implications. Whereas a major research focus lies on the detection
of outdoor fires, indoor camera-based fire detection is still an open issue.
Cameras in combination with computer vision helps to detect flames and
smoke more quickly than conventional fire detectors. In this work, we present
a computer vision-based smoke detection algorithm based on contrast changes
and a multi-step classification. This work accelerates computer vision-based
fire detection considerably in comparison with classical indoor-fire detection.