Shot boundary detection in the presence of fire flicker and explosion using stationary wavelet transform

Detection of fire in video for fire alarm systems has been studied by many researchers, but detection of shot boundaries under fire, flicker and explosion (FFE) is one of the under-studied areas. In thriller movies, FFE occur more often than other special effects and lead to false detection of shot boundary. We tested major metrics used for detection of shot boundaries under FFE for various movies. It is observed that for almost all metrics, precision is low due to false positives caused by FFE. We propose an algorithm based on cross-correlation coefficient, stationary wavelet transform and combination of local and adaptive thresholds for detection of shot boundaries under FFE. The proposed algorithm is tested on three movies, and experimental results validate the effectiveness of our proposed method in terms of better recall and precision.

[1]  John S. Boreczky,et al.  Comparison of video shot boundary detection techniques , 1996, J. Electronic Imaging.

[2]  Rangachar Kasturi,et al.  Machine vision , 1995 .

[3]  Rainer Lienhart,et al.  Comparison of automatic shot boundary detection algorithms , 1998, Electronic Imaging.

[4]  Alan Hanjalic,et al.  Shot-boundary detection: unraveled and resolved? , 2002, IEEE Trans. Circuits Syst. Video Technol..

[5]  Nilesh V. Patel,et al.  Statistical approach to scene change detection , 1995, Electronic Imaging.

[6]  Antonio Albiol,et al.  Low complexity cut detection in the presence of flicker , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[7]  Atreyi Kankanhalli,et al.  Automatic partitioning of full-motion video , 1993, Multimedia Systems.

[8]  R. Todd Ogden.  Elementary Statistical Applications , 1997 .

[9]  Hasan Demirel,et al.  Fire detection in video sequences using a generic color model , 2009 .

[10]  Turgay Çelik,et al.  Fire detection using statistical color model in video sequences , 2007, J. Vis. Commun. Image Represent..

[11]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Markus Loepfe,et al.  An image processing technique for fire detection in video images , 2006 .

[13]  R. Ogden,et al.  Essential Wavelets for Statistical Applications and Data Analysis , 1996 .

[14]  Stefano Spaccapietra,et al.  Visual Database Systems 3 , 1995, IFIP — The International Federation for Information Processing.

[15]  Ebroul Izquierdo,et al.  Efficient visual fire detection applied for video retrieval , 2008, 2008 16th European Signal Processing Conference.

[16]  B. Silverman,et al.  The Stationary Wavelet Transform and some Statistical Applications , 1995 .

[17]  Akio Nagasaka,et al.  Automatic Video Indexing and Full-Video Search for Object Appearances , 1991, VDB.

[18]  Gye-Young Kim,et al.  Robust Scene Change Detection Algorithm for Flashlights , 2007, ICCSA.

[19]  Bo Zhang,et al.  A Formal Study of Shot Boundary Detection , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[20]  O. Rioul,et al.  Wavelets and signal processing , 1991, IEEE Signal Processing Magazine.

[21]  A. Enis Çetin,et al.  Computer vision based method for real-time fire and flame detection , 2006, Pattern Recognit. Lett..