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Shot boundary detection using perceptual and semantic information

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Abstract

The paper proposes a shot boundary detection system using Gist and local descriptor. Gist provides the perceptual and conceptual information of a scene. The proposed system can be roughly divided into three steps. The first step consists of forming of groups of frames by calculating the correlation of the Gist features between consecutive frames of the video. Secondly, abrupt transitions are found out using the group (G), MSER and a threshold (for abrupt separately, \(th_{cut}\)). And lastly, gradual transitions of the video are found using triangular pattern matching. We have performed the experiment on TRECVid 2001 and 2007 dataset. The novel contribution of this paper is that the proposed system shows an activity-based shot boundary detection where only the possible transition regions of a video are considered for shot detection. This approach reduces the computational complexity by processing the transition regions only. We have achieved better results in terms of F1, precision and recall, when compared to previously published approaches.

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References

  1. Anjulan A, Canagarajah N (2007) Object based video retrieval with local region tracking. Signal Process Image Commun 22(7–8):607–621

    Article  Google Scholar 

  2. Baber J, Afzulpurkar N, Dailey M, Bakhtyar M (2011) Shot boundary detection from videos using entropy and local descriptor. In: 17th International conference on digital signal processing (DSP), pp 1–6

  3. Bhowmick B, Chattopadhyay D (2009) Shot boundary detection using texture feature based on co-occurrence matrices. In: International multimedia, signal processing and communication technologies, pp 165–168

  4. Boccignone G, Chianese A, Moscato V, Picariello A (2005) Foveated shot detection for video segmentation. IEEE Trans Circuits Syst Video Technol 15(3):365–377

    Article  Google Scholar 

  5. Du Q, Zheng H, Zhang S (2009) Motion estimation of projected spatio-temporal slice for shot boundary detection. In: 7th International conference on information, communications and signal processing, pp 1–5

  6. Hameed A (2009) A novel framework of shot boundary detection for uncompressed videos. In: International conference on emerging technologies, pp 274–279

  7. Hu W, Xie N, Li L, Zeng X, Maybank S (2011) A survey on visual content-based video indexing and retrieval. IEEE Trans Syst Man Cybern Part C Appl Rev 41(6):797–819

    Article  Google Scholar 

  8. Jadon R, Chaudhury S, Biswas K (2001) A fuzzy theoretic approach for video segmentation using syntactic features. Pattern Recognit Lett 22(13):1359–1369

    Article  MATH  Google Scholar 

  9. Jhuang H, Chikkerur S (2006) Video shot boundary detection using gist

  10. Koprinska I, Carrato S (2001) Temporal video segmentation: a survey. Signal Process Image Commun 16(5):477–500

    Article  Google Scholar 

  11. Lee S-W, Kim Y-M, Choi SW (2000) Fast scene change detection using direct feature extraction from mpeg compressed videos. IEEE Trans Multimed 2(4):240–254

    Article  Google Scholar 

  12. Li Y-N, Lu Z-M, Niu X-M (2009) Fast video shot boundary detection framework employing pre-processing techniques. IET Image Process 3(3):121–134

    Article  Google Scholar 

  13. Lu Z-M, Shi Y (2013) Fast video shot boundary detection based on svd and pattern matching. IEEE Trans Image Process 22(12):5136–5145

    Article  MathSciNet  Google Scholar 

  14. Mas J, Fernandez G (2003) Video shot boundary detection based on color histogram. In: Notebook Papers TRECVID2003

  15. Matas J, Chum O, Urban M, Pajdla T (2004) Robust wide-baseline stereo from maximally stable extremal regions. Image Vis Comput 22(10):761–767 British Machine Vision Computing

    Article  Google Scholar 

  16. Meng J, Juan Y, Chang S-F (1995) Scene change detection in a mpeg compressed video sequence. In: Proceedings of the SPIE in digital video compression: algorithms and technologies 2419:14–25

  17. Luo M, DeMenthon D, Doermann D (2004) Shot boundary detection using pixel-to-neighbour image differences in video. In: TRECVID 2004Workshop Notebook Papers

  18. Mohanta P, Saha S, Chanda B (2012) A model-based shot boundary detection technique using frame transition parameters. IEEE Trans Multimed 14(1):223–233

    Article  Google Scholar 

  19. Oliva A (2005) Gist of the scene. In: Itti L, Rees G, Tsotsos JK (eds) The encyclopedia of neurobiology of attention. Elsevier, Amsterdam, pp 251–256

    Chapter  Google Scholar 

  20. Oliva A, Torralba A (2001) Modeling the shape of the scene: a holistic representation of the spatial envelope. Int J Comput Vis 42(3):145–175

    Article  MATH  Google Scholar 

  21. Panchal P, Merchant S, Patel N (2012) Scene detection and retrieval of video using motion vector and occurrence rate of shot boundaries. In: 2012 Nirma University International conference on engineering (NUiCONE), pp 1–6

  22. Smeaton AF, Over P, Doherty AR (2010) Video shot boundary detection: seven years of TRECVid activity. Comput Vis Image Underst 114(4):411–418

    Article  Google Scholar 

  23. Thounaojam DM, Khelchandra T, Singh KM, Roy S (2016) A genetic algorithm and fuzzy logic approach for video shot boundary detection. Computational Intelligence and Neuroscience, vol 2016, Article ID 8469428

  24. Thounaojam DM, Trivedi A, Manglem Singh K, Roy S (2014) A survey on video segmentation. In: Mohapatra DP, Patnaik S (eds) Intelligent computing, networking, and informatics, vol 243., Advances in intelligent systems and computingSpringer, India, pp 903–912

    Chapter  Google Scholar 

  25. Wen Y, Li Z, Chen J, Zhao H (2013) A prediction algorithm for real-time video traffic based on wavelet packet. In: Su J, Zhao B, Sun Z, Wang X, Wang F, Xu K (eds) Frontiers in internet technologies, vol 401., Communications in computer and information scienceSpringer, Berlin, pp 1–8

    Chapter  Google Scholar 

  26. Yunbo R, Leiting C (2012) A survey of video enhancement techniques. J Inf Hiding Multimed Signal Process 3(1):71–99

    Google Scholar 

  27. Zhang H, Hu R, Song L (2011) A shot boundary detection method based on color feature. In: International conference on computer science and network technology (ICCSNT), 2011, vol 4, pp 2541–2544

  28. Zhang H, Kankanhalli A, Smoliar S (1993) Automatic partitioning of full-motion video. Multimed Syst 1(1):10–28

    Article  Google Scholar 

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Acknowledgements

Sound and Vision video is copyrighted. The Sound and Vision video used in this work is provided solely for research purposes through the TREC Video Information Retrieval Evaluation Project Collection.

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Authors and Affiliations

  1. National Institute of Technology Silchar, Silchar, Assam, India

    Dalton Meitei Thounaojam

  2. National Institute of Technology Agartala, West Tripura, Tripura, India

    Vivek Singh Bhadouria

  3. Assam University Silchar, Silchar, Assam, India

    Sudipta Roy

  4. National Institute of Technology Manipur, Imphal, India

    Kh. Manglem Singh

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  1. Dalton Meitei Thounaojam
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  2. Vivek Singh Bhadouria
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  3. Sudipta Roy
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  4. Kh. Manglem Singh
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Correspondence to Dalton Meitei Thounaojam.

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Thounaojam, D.M., Bhadouria, V.S., Roy, S. et al. Shot boundary detection using perceptual and semantic information. Int J Multimed Info Retr 6, 167–174 (2017). https://doi.org/10.1007/s13735-017-0123-1

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  • DOI: https://doi.org/10.1007/s13735-017-0123-1

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