Abstract
In this paper, we present VSCAN, a novel approach for generating static video summaries. This approach is based on a modified DBSCAN clustering algorithm to summarize the video content utilizing both color and texture features of the video frames. The paper also introduces an enhanced evaluation method that depends on color and texture features. Video Summaries generated by VSCAN are compared with summaries generated by other approaches found in the literature and those created by users. Experimental results indicate that the video summaries generated by VSCAN have a higher quality than those generated by other approaches.
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IEEE Standard Glossary of Image Processing and Pattern Recognition Terminology, IEEE Std. 610.4-1990 (1990)
Aherne, F.J., Thacker, N.A., Rockett, P.I.: The bhattacharyya metric as an absolute similarity measure for frequency coded data. Kybernetika 34(4), 363–368 (1998)
de Avila, S.E.F., Lopes, A.P.B., et al.: Vsumm: A mechanism designed to produce static video summaries and a novel evaluation method. Pattern Recognition Letters 32(1), 56–68 (2011)
Blanken, H.M., De Vries, A.P., Blok, H.E., Feng, L.: Multimedia retrieval. Springer, Heidelberg (2007)
DeMenthon, D., Kobla, V., Doermann, D.: Video summarization by curve simplification. In: Proceedings of the Sixth ACM International Conference on Multimedia, pp. 211–218. ACM Press (1998)
Ester, M., Kriegel, H.P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proceedings of the 2nd International Conference on Knowledge Discovery and Data mining, vol. 1996, pp. 226–231. AAAI Press (1996)
Furini, M., Geraci, F., Montangero, M., Pellegrini, M.: Stimo: Still and moving video storyboard for the web scenario. Multimedia Tools and Applications 46(1), 47–69 (2010)
Girgensohn, A., Boreczky, J., Wilcox, L.: Keyframe-based user interfaces for digital video. Computer 34(9), 61–67 (2001)
Kailath, T.: The divergence and bhattacharyya distance measures in signal selection. IEEE Transactions on Communication Technology 15(1), 52–60 (1967)
Liu, T., Zhang, X., Feng, J., Lo, K.T.: Shot reconstruction degree: a novel criterion for key frame selection. Pattern Recognition Letters 25(12), 1451–1457 (2004)
Mundur, P., Rao, Y., Yesha, Y.: Keyframe-based video summarization using delaunay clustering. International Journal on Digital Libraries 6(2), 219–232 (2006)
Parimala, M., Lopez, D., Senthilkumar, N.: A survey on density based clustering algorithms for mining large spatial databases. International Journal of Advanced Science and Technology 31, 59–66 (2011)
Pfeiffer, S., Lienhart, R., Fischer, S., Effelsberg, W.: Abstracting digital movies automatically. Journal of Visual Communication and Image Representation 7(4), 345–353 (1996)
Singha, M., Hemachandran, K.: Signal & image processing: An international journal (sipij). Content Based Image Retrieval using Color and Texture 3(1), 39–57 (2012)
Smith, J.R., Chang, S.F.: Transform features for texture classification and discrimination in large image databases. In: Proceedings of the IEEE International Conference on Image Processing, ICIP 1994, vol. 3, pp. 407–411 (1994)
Stanković, R.S., Falkowski, B.J.: The haar wavelet transform: its status and achievements. Computers & Electrical Engineering 29(1), 25–44 (2003)
Stehling, R.O., Nascimento, M.A., Falcao, A.X.: Techniques for color-based image retrieval. Multimedia Mining, 61–82 (2002)
Swain, M.J., Ballard, D.H.: Color indexing. International Journal of Computer Vision 7(1), 11–32 (1991)
Truong, B.T., Venkatesh, S.: Video abstraction: A systematic review and classification. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) 3(1), 3 (2007)
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Mahmoud, K.M., Ismail, M.A., Ghanem, N.M. (2013). VSCAN: An Enhanced Video Summarization Using Density-Based Spatial Clustering. In: Petrosino, A. (eds) Image Analysis and Processing – ICIAP 2013. ICIAP 2013. Lecture Notes in Computer Science, vol 8156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41181-6_74
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DOI: https://doi.org/10.1007/978-3-642-41181-6_74
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