Shot Boundary Detection Algorithm Based on Multi-Feature Fusion

Article Preview

Abstract:

To establish a general and robust shot boundary detection algorithm, according to characteristics of lens conversion and the ideal of multiple video features fusion, a shot boundary detection algorithm is proposed based on YUV histogram, texture feature and edge orientation histogram in the paper. Besides, global and self-adaptive threshold are combined to use so as to control the process of shot boundary detection and enhance the accuracy of threshold selection. The experiment results show that the algorithm can effectively realize video shot boundary detection and strengthen the robustness of the detection.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

3866-3871

Citation:

Online since:

August 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] CERNEKOVA Z, PITAS I, NIKOU C. Information theory-based shot cut/fade detection and video summarization[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2006, 16(1): 82-91.

DOI: 10.1109/tcsvt.2005.856896

Google Scholar

[2] Feng Hong-cai, Yuan Xiao-juan, Ming Wei. A shot boundary detection method based on color space[C]. International Conference on E-Business and E-Government, 2010, pp.1647-1650.

DOI: 10.1109/icee.2010.417

Google Scholar

[3] Wang Cheng-ru, Wang Hui-hui. MPEG video shot boundary detection based on motion vectors[J]. Journal of Computer Applications, 2012, 32(5): 1269-1271.

DOI: 10.3724/sp.j.1087.2012.01269

Google Scholar

[4] Liu Qun, Jiang Wei, Wu Yu. Approach of shot-boundary detection based on multi-feature fusion[J]. Computer Engineering and Application, 2010, 46(13): 171-174.

Google Scholar

[5] Jin-Wook Lee, Jae-Soo Cho. Effective Lane detection and tracking method using statistical modeling of color and lane edge-orientation[J]. Advanced Information Sciences and Service Sciences, 2010, 3(2): 40-47.

DOI: 10.4156/aiss.vol2.issue3.6

Google Scholar

[6] Sun Shi-ran, Ai Si Ka Er AMDL, Liu Wen-Hua. Image retrieval based on the entropy value and the Gabor filter[J]. Laser Journal, 2011, 32(2): 24-26.

Google Scholar

[7] Qingshan Yang, Chengan Guo. Fuzzy ensemble of local Gabor sparse representation classifiers for face recognition[J]. Advanced Information Sciences and Service Sciences, 2011, 10(3): 345-354.

DOI: 10.4156/aiss.vol3.issue10.43

Google Scholar

[8] Jiang Wei, Chen Hui. New edge detection model based on fractional differential and Sobel operator[J]. Computer Engineering and Application, 2012, 48(4): 182-185.

Google Scholar

[9] Miyazawa M, Peifeng Zeng, et al. A systolic algorithm for euclidean distance transform[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(7): 1127-1134.

DOI: 10.1109/tpami.2006.133

Google Scholar

[10] Ren Jinchang, Jiang Jianmin, Chen Juan. Shot boundary detection in MPEG videos using local and Global indicators[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2009, 19(8): 1234-1238.

DOI: 10.1109/tcsvt.2009.2022707

Google Scholar

[11] Pan Chen-ming, Chuang Yung-yu, Wisnton H. Hsu. NTU TRECVID-2007 fast rushes summarization system[C]. International workshop on TRECVID video summarization, 2007, pp: 74-78.

DOI: 10.1145/1290031.1290045

Google Scholar