{"title":"Shot Boundary Detection Using Octagon Square Search Pattern ","authors":"J. Kavitha, S. Sowmyayani, P. Arockia Jansi Rani","volume":115,"journal":"International Journal of Computer and Information Engineering","pagesStart":1409,"pagesEnd":1413,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10006036","abstract":"
In this paper, a shot boundary detection method is presented using octagon square search pattern. The color, edge, motion and texture features of each frame are extracted and used in shot boundary detection. The motion feature is extracted using octagon square search pattern. Then, the transition detection method is capable of detecting the shot or non-shot boundaries in the video using the feature weight values. Experimental results are evaluated in TRECVID video test set containing various types of shot transition with lighting effects, object and camera movement within the shots. Further, this paper compares the experimental results of the proposed method with existing methods. It shows that the proposed method outperforms the state-of-art methods for shot boundary detection.<\/p>\r\n","references":"[1]\tSklar, Robert. Film: An International History of the Medium. (London): Thames and Hudson, (c. 1990). p. 526.\r\n[2]\tAlan Hanjalic, \u201cShot Boundary detection: Unraveled and Resolved?\u201d, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 12, No. 2, February 2002.\r\n[3]\tH. Zhang and S. Kankanhalli, \u201cAutomatic partitioning of full-motion video,\u201d ACM Journal of Multimedia Systems, vol. 1, pp. 10\u201328, Jan. 1993.\r\n[4]\tR. Zabih, J. Miller, and K. Mai, \u201cA feature-based algorithm for detecting cuts and classifying scene breaks,\u201d in Proc. ACM Multimedia \u201995, San Francisco, CA, pp. 189\u2013200, 1995.\r\n[5]\tB. Shahraray, \u201cScene change detection and content-based sampling of video sequences,\u201d Proc. SPIE, vol. 2419, pp. 2\u201313, Apr. 1995.\r\n[6]\tA. Hampapur, R. Jain, T. Weymouth, Production model based digital video segmentation, J. Multimedia Tools Appl. 1 (1) (1995) 9\u201346.\r\n[7]\tU. Gargi, R. Kasturi, and S. H. Strayer, \u201cPerformance characterization of video-shot-change detection methods,\u201d IEEE Trans. Circuits, Systems, Video Technology, vol. 10, pp. 1\u201313, Feb. 2000.\r\n[8]\tR. Lienhart, \u201cReliable transition detection in videos: A survey and practitioner\u2019s guide,\u201d Int. Journal of Image and Graphics, vol. 1, pp. 469\u2013486, Sept. 2001.\r\n[9]\tWeigang Zhang, et. al., \u201cVideo Shot Detection Using Hidden Markov Models with Complementary Features,\u201d In Pro-ceedings of the First International Conference on Innovative Computing, Information and Control. Vol.3. http:\/\/doi.ieeecomputersociety.org\/10.1109\/ICICIC.2006.549, 2006. \r\n[10]\tY. Kawai, H. Sumiyoshi, and N. Yagi. \u201cShot Boundary De-tection at TRECVID 2007,\u201d In TRECVID 2007 Workshop, Gaithersburg, 2007.\r\n[11]\tDon, A., Uma, K. Adaptive edge-oriented shot boundary detection. EURASIP Journal on Image and Video Processing 2009.\r\n[12]\tShiguo Lian, \u201cAutomatic video temporal segmentation based on multiple features,\u201d Soft Comput., vol. 15, no. 3, pp. 469\u2013482, 2011.\r\n[13]\tG. G. Lakshmi Priya , S. Domnic, \u201cTransition Detection Using Hilbert Transform and Texture Features\u201d, American Journal of Signal Processing, 2012, 2(2): 35-40.\r\n[14]\tChoudhury, A., Medioni. G.: \"A framework for Robust Online Video Contrast Enhancement Using Modularity Optimization,\" Circuits and Systems for Video Technology, IEEE Transactions on, 2012, (22), 9, pp. 1266 \u2013 1279. \r\n[15]\tB.H. Shekar and K.P. Uma, \u201cKirsch directional derivatives based shot boundary detection: an efficient and accurate method\u201d, Procedia Computer Science, pp. 565-571, 2015.\r\n[16]\tSowmyayani. S., Arockia Jansi Rani, P., \u201cBlock based Motion Estimation using Octagon and Square Pattern\u201d, Int. Journal of Signal Processing., Image Processing and Pattern Recognition, vol. 7, no. 4, pp.317-324, 2014.\r\n[17]\tKavitha. J, Sowmyayani. S., Arockia Jansi Rani. P., \u201cShot Boundary Detection Using DWT and Texture Features\u201d, IEEE International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE\u201916).\r\n[18]\tOpen Video Project (OVP) (online) http:\/\/www.open-video.org\/.\r\n[19]\tTRECVID Dataset (online) http:\/\/trecvid.nist.gov\/.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 115, 2016"}