Shot Cut Test Based on Mathematics Parameter and Chain Code

Abstract:

In this paper, An effective shot cut detection algorithm directly in DCT domain was proposed. This algorithm(including abrupt change and ) test the n -1 frame and n frame through the extracting the feature vector of each frame. When extract the features of frame, two-dimensional mathematics parameter m1-s from DCT coefficients without its inverse transform and 8 directional chain code was computed, Divide m1-s space into 30 unequal partitions (subspaces) and compute the numbers pr within the 30 subspaces (entries) as the feature vector to judge the different of the two frames. locating shot cuts is operated by comparison tests.

• Periodical: Advanced Materials Research (Volumes 712-715)
• Pages: 2399-2402
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.712-715.2399
• Online since: June 2013
• Authors: Jian Feng Wang, Xiao Rong Zhao
• Keywords: Chain Code, DCT, Histogram, Mathematics Parameter, Shot Cut

References

[1] I. Daubechies, M. Defrise, and C. De Mol, "An iterative thresholding algorithm for linear inverse problems with a sparsity constraint," Commun. Pure Appl. Math., vol. 57, p.1416–1457, 2004.

DOI: 10.1002/cpa.20042

[2] L. Vincent and P. Soille, "Watersheds in digital spaces: an efficient algorithm based immersion simulations," IEEE Trans on PAMI, Vol. No6, pp.583-598,(2008)

DOI: 10.1109/34.87344

[3] S. S. Chen, D. Donoho, and M. Saunders, "Atomic decomposition by basis pursuit," SIAM J. Sci. Comput., vol. 20, no. 1, 1998.

DOI: 10.1137/s1064827596304010

[4] D. Teropoulos and K. Fleischer, "Deformable models," Vis. Comput., Vol,4, pp.306-331,2007.

[5] A. Destrero, C. De Mol, F. Odone, and A. Verri, Y. Yagi, Ed. et al.,"A regularized approach to feature selection for face detection," in Proc. Asian Conf. Computer Vision, ACCV, 2007, vol. 4844, LNCS, p.881–890.

DOI: 10.1007/978-3-540-76390-1_86

[6] Ramin Zabih, Justin Miller and Kevin Mai, "A feature-based algorithm for detecting and classifying production effects", Multimedia Systems ,Vol.6,No.2, 2005 , pp.119-128

DOI: 10.1007/s005300050115

[7] Shu-Ching Chen, Mei-Ling Shyu, Cheng-Cui Zhang and R.L. Kashyap, "Video scene change detection method using unsuper segmentation and object tracking"，IEEE International Conference on Multimedia and Expo(ICME), 2001, pp.57-60

DOI: 10.1109/icme.2001.1237654

[8] JungHwan, Kien A.Hua, Ning Liang, "A content-based shot cut detection and classification technique using background tracking" , Proc. of IS&T Conference on Multimedia Computing and Networking 2000, San Jose CA, January 2000, pp.254-265

[9] N. de Freitas, R. Dearden, F. Hutter, R. M.-Menendez, J. Mutch, and D. Poole, "Diagnosis by a waiter and a Mars explorer," Proc. IEEE, vol. 92, no. 3, p.455–468, Mar. 2004.

DOI: 10.1109/jproc.2003.823157

[10] D. Schulz, D. Fox, and J. Hightower, "People tracking with anonymous and id-sensors using Rao-Blackwellized particle filters," presented atthe Int. Joint Conf. Artificial Intelligence (IJCAI), 2003.

[11] I. Guyon and E. Elisseeff, "An introduction to variable and feature selection," J. Mach. Learn. Res., vol. 3, p.1157–1182, 2003.

[12] B. Heisele, T. Serre, S. Mukherjee, and T. Poggio, "Feature reduction and hierarchy of classifiers for fast object detection in video images," presented at the IEEE CVPR, 2001.

DOI: 10.21236/ada458821