Video Shot Detection and Key Frame Extraction Using Faber Shauder DWT and SVD

Key frame extraction methods select the most
representative frames of a video, which can be used in different areas
of video processing such as video retrieval, video summary, and video
indexing. In this paper we present a novel approach for extracting key
frames from video sequences. The frame is characterized uniquely by
his contours which are represented by the dominant blocks. These
dominant blocks are located on the contours and its near textures.
When the video frames have a noticeable changement, its dominant
blocks changed, then we can extracte a key frame. The dominant
blocks of every frame is computed, and then feature vectors are
extracted from the dominant blocks image of each frame and arranged
in a feature matrix. Singular Value Decomposition is used to calculate
sliding windows ranks of those matrices. Finally the computed ranks
are traced and then we are able to extract key frames of a video.
Experimental results show that the proposed approach is robust
against a large range of digital effects used during shot transition.





References:
[1] M. El Hajji, H. Douzi, D. Mammas, R. Harba, F. Ros, A New Image
Watermarking Algorithm Based on Mixed Scales Wavelets, J. Electron.
Imaging. 21(1), 013003 (Feb 27, 2012).
[2] M. Hajji , H. Douzi , R. Harba, Watermarking Based on the Density
Coefficients of Faber Schauder Wavelets, Proceedings of the 3rd
international conference on Image and Signal Processing, July 01-03,
2008, Cherbourg-Octeville, France.
[3] W. Abd-Almageed, Online, simultaneous shot boundary detection and key
frame extraction for sports videos using rank tracing, Image Processing,
2008. ICIP 2008. 15th IEEE International Conference on, vol., no.,
pp.3200,3203, 12-15 Oct. 2008.
[4] S. Lei, G. Xie, G. Yan, A Novel Key-Frame Extraction Approach for
Both Video Summary and Video Index , ScientificWorldJournal. 2014
Mar 16;2014:695168.
[5] B. T. Truong, Venkatesh, Video abstraction: A systematic review and
classification, ACM Trans. Multimedia Comput. Commun. Appl. 3, 1,
Article 3, Feb. 2007.
[6] C. T. Dang, M. Kumar, H. Radha, Key Frame Extraction from Consumer
Videos Using Epitome, Image Processing (ICIP), 19th IEEE International
Conference on. pp. 93-96, September 2012.
[7] H. Douzi, D. Mammass, F. Nouboud, ”Faber-Schauder wavelet
transformation application to edge detection and image characterization,”
Journal of Mathematical Imaging and Vision Kluwer Academic Press, pp
91-102 ,Vol. 14(2), 2001.
[8] W. Sweldens, ”The lifting scheme: A construction of second generation
wavelets,” SIAM Journal on Mathematical Analysis, vol. 29, no.2, pp.
511546, 1998.
[9] N. Otsu, A threshold selection method from grey scale histogram, IEEE
Trans. on SMC, Vol. 1, pp. 62-66, 1979.
[10] K. Bhagyashri, Joshi M. Y. ,Robust Image Watermarking based on
Singular Value Decomposition and Discrete Wavelet Transform, Nanded
2010 IEEE.