Abstract
In this paper we present the methods used for the analysis of video based on mutual information. We propose a novel method of abrupt cut detection and a novel objective method for measuring the quality of video. In the field of abrupt cut detection we improve the existing method based on mutual information. The novelty of our method is in combining the motion prediction and the mutual information. Our approach provides higher robustness to object and camera motion. According to the objective method for measuring the quality of video, it is based on calculation the mutual information between the frame from the original sequence and the corresponding frame from the test sequence. We compare results of the proposed method with commonly used objective methods for measuring the video quality. Results show that our method correlates with the standardized method and the distance metric, so it is possible to replace a more complex method with our simpler method.
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References
ITU-R BT.500-11, Recommmendation ITU-R (2002)
Winkler, S.: Digital video quality vision model and metrics. John Wiley & Sons Ltd., Chichester (2005)
Kawayoke, Y., Horita, Y.: NR objective continuous video quality assessment model based on frame quality measure. University of Toyama, Japan
Ries, M., Nemethova, O., Rupp, M.: Video quality estimation for mobile H.264/AVC video streaming. Journal of communication 3, 41–50 (2008)
Amiri, A., Fathy, M.: Video shot boundary detection using QR-decomposition and Gaussian transition detection. EURASIP Journal on Advances in Signal Processing 2009, Article ID 509438
Hanjalic, A.: Shot-boundary detection: unraveled and resolved? IEEE Transactions on Circuits and Systems for Video Technology 12(2), 90–105 (2002)
Boreczky, J.S., Rowe, L.A.: Comparison of video shot boundary detection techniques. In: Proc. SPIE in Storage and Retrieval for Still Image and Video Databases IV, vol. 2664, pp. 170–179 (January 1996)
Lienhart, R.: Comparison of automatic shot boundary detection algorithms. In: Proceedings of SPIE in Storage and Retrieval for Image and Video Databases VII, San Jose, Ca, USA, vol. 3656, pp. 290–301 (January 1999)
Paschalakis, S., Simmons, D.: Detection of gradual transitions in video sequences (April 24, 2008), http://www.wipo.int/pctdb/en/wo.jsp?WO=2008046748
Cernekova, Z.: Temporal video segmentation and video summarization, Ph.D. dissertation, Dept. App. Inf., Comenius Univ., Bratislava, SK (2009)
Zhao, H., Li, X., Yu, L.: Shot boundary detection based on mutual information and canny edge detector. In: Proc. 2008 International Conference on Computer Science and Software Engineering (2008)
Xiao, F.: DCT-based Video Quality Evaluation, MSU Graphics and Media Lab. (Video Group) (Winter 2000)
Wang, Y.: Survey of objective video quality measurements, EMC Corp., Hopkinton, MA, Tech. Rep. WPI-CS-TR-06-02 (2006)
Dosselmann, R., Yang, D.X.: A Formal Assessment of the Structural Similarity Index, Technical Report TR-CS 2008-2. University of Regina, Regina (2008)
Rubner, Y., Tomasi, C., Guibas, L.J.: The earth mover’s distance as a metric for image retrieval. International Journal of Computer Vision 40(2), 99–121 (2000)
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Krulikovská, L., Mardiak, M., Pavlovic, J., Polec, J. (2010). Video Analysis Based on Mutual Information. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2010. Lecture Notes in Computer Science, vol 6375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15907-7_10
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DOI: https://doi.org/10.1007/978-3-642-15907-7_10
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