Multi-modal time-of-flight based fire detection
- Author
- Steven Verstockt (UGent) , Sofie Van Hoecke (UGent) , Pieterjan De Potter (UGent) , Peter Lambert (UGent) , Charles Hollemeersch (UGent) , Bart Sette, Bart Merci (UGent) and Rik Van de Walle (UGent)
- Organization
- Abstract
- This paper proposes two novel time-of-flight based fire detection methods for indoor and outdoor fire detection. The indoor detector is based on the depth and amplitude image of a time-of-flight camera. Using this multi-modal information, flames can be detected very accurately by fast changing depth and amplitude disorder detection. In order to detect the fast changing depth, depth differences between consecutive frames are accumulated over time. Regions which have multiple pixels with a high accumulated depth difference are labeled as candidate flame regions. Simultaneously, the amplitude disorder is also investigated. Regions with high accumulative amplitude differences and high values in all detail images of the amplitude image its discrete wavelet transform, are also labeled as candidate flame regions. Finally, if one of the depth and amplitude candidate flame regions overlap, fire alarm is given. The outdoor detector, on the other hand, only differs from the indoor detector in one of its multi-modal inputs. As depth maps are unreliable in outdoor environments, the outdoor detector uses a visual flame detector instead of the fast changing depth detection. Experiments show that the proposed detectors have an average flame detection rate of 94% with no false positive detections.
- Keywords
- time of flight imaging, multi-modal, fire detection, image registration, multi-sensor, video surveillance, flame features, VIDEO, REGISTRATION, RECOGNITION, FRAMEWORK, TRACKING, STEREO, CAMERA, COLOR
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-3232719
- MLA
- Verstockt, Steven, et al. “Multi-Modal Time-of-Flight Based Fire Detection.” MULTIMEDIA TOOLS AND APPLICATIONS, vol. 69, no. 2, 2014, pp. 313–38, doi:10.1007/s11042-012-0991-6.
- APA
- Verstockt, S., Van Hoecke, S., De Potter, P., Lambert, P., Hollemeersch, C., Sette, B., … Van de Walle, R. (2014). Multi-modal time-of-flight based fire detection. MULTIMEDIA TOOLS AND APPLICATIONS, 69(2), 313–338. https://doi.org/10.1007/s11042-012-0991-6
- Chicago author-date
- Verstockt, Steven, Sofie Van Hoecke, Pieterjan De Potter, Peter Lambert, Charles Hollemeersch, Bart Sette, Bart Merci, and Rik Van de Walle. 2014. “Multi-Modal Time-of-Flight Based Fire Detection.” MULTIMEDIA TOOLS AND APPLICATIONS 69 (2): 313–38. https://doi.org/10.1007/s11042-012-0991-6.
- Chicago author-date (all authors)
- Verstockt, Steven, Sofie Van Hoecke, Pieterjan De Potter, Peter Lambert, Charles Hollemeersch, Bart Sette, Bart Merci, and Rik Van de Walle. 2014. “Multi-Modal Time-of-Flight Based Fire Detection.” MULTIMEDIA TOOLS AND APPLICATIONS 69 (2): 313–338. doi:10.1007/s11042-012-0991-6.
- Vancouver
- 1.Verstockt S, Van Hoecke S, De Potter P, Lambert P, Hollemeersch C, Sette B, et al. Multi-modal time-of-flight based fire detection. MULTIMEDIA TOOLS AND APPLICATIONS. 2014;69(2):313–38.
- IEEE
- [1]S. Verstockt et al., “Multi-modal time-of-flight based fire detection,” MULTIMEDIA TOOLS AND APPLICATIONS, vol. 69, no. 2, pp. 313–338, 2014.
@article{3232719, abstract = {{This paper proposes two novel time-of-flight based fire detection methods for indoor and outdoor fire detection. The indoor detector is based on the depth and amplitude image of a time-of-flight camera. Using this multi-modal information, flames can be detected very accurately by fast changing depth and amplitude disorder detection. In order to detect the fast changing depth, depth differences between consecutive frames are accumulated over time. Regions which have multiple pixels with a high accumulated depth difference are labeled as candidate flame regions. Simultaneously, the amplitude disorder is also investigated. Regions with high accumulative amplitude differences and high values in all detail images of the amplitude image its discrete wavelet transform, are also labeled as candidate flame regions. Finally, if one of the depth and amplitude candidate flame regions overlap, fire alarm is given. The outdoor detector, on the other hand, only differs from the indoor detector in one of its multi-modal inputs. As depth maps are unreliable in outdoor environments, the outdoor detector uses a visual flame detector instead of the fast changing depth detection. Experiments show that the proposed detectors have an average flame detection rate of 94% with no false positive detections.}}, author = {{Verstockt, Steven and Van Hoecke, Sofie and De Potter, Pieterjan and Lambert, Peter and Hollemeersch, Charles and Sette, Bart and Merci, Bart and Van de Walle, Rik}}, issn = {{1380-7501}}, journal = {{MULTIMEDIA TOOLS AND APPLICATIONS}}, keywords = {{time of flight imaging,multi-modal,fire detection,image registration,multi-sensor,video surveillance,flame features,VIDEO,REGISTRATION,RECOGNITION,FRAMEWORK,TRACKING,STEREO,CAMERA,COLOR}}, language = {{eng}}, number = {{2}}, pages = {{313--338}}, title = {{Multi-modal time-of-flight based fire detection}}, url = {{http://doi.org/10.1007/s11042-012-0991-6}}, volume = {{69}}, year = {{2014}}, }
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