Flame detection method in video using covariance descriptors
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
1817 - 1820
Item Usage Stats
MetadataShow full item record
Video fire detection system which uses a spatio-temporal covariance matrix of video data is proposed. This system divides the video into spatio-temporal blocks and computes covariance features extracted from these blocks to detect fire. Feature vectors taking advantage of both the spatial and the temporal characteristics of flame colored regions are classified using an SVM classifier which is trained and tested using video data containing flames and flame colored objects. Experimental results are presented. © 2011 IEEE.
support vector machines
Fire detection systems
Support vector machines
Published Version (Please cite this version)http://dx.doi.org/10.1109/ICASSP.2011.5946857
Showing items related by title, author, creator and subject.
Verstockt, S.; Hoecke, S. V.; Beji, T.; Merci, B.; Gouverneur, B.; Cetin, A. E.; Potter, P. D.; Walle, R. V. D. (Elsevier, 2013)In this paper a novel multi-modal flame and smoke detector is proposed for the detection of fire in large open spaces such as car parks. The flame detector is based on the visual and amplitude image of a time-of-flight ...
Acar, C.; Atlas, A.; Çevik, K.; Ölmez I.; Ünlü, M.; Özkan, D.; Duygulu P. (2007)People are the most important subjects in news videos and for proper retrieval of people images; face detection is a very crucial step. However, face detection and recognition in news videos is a very challenging task due ...
Yazar, A.; Enis Çetin, A. (2013)Intelligent ambient assisted living systems for elderly and handicapped people become affordable with the recent advances in computer and sensor technologies. In this paper, fall detection algorithm using multiple passive ...