Abstract
In this paper, a content-aware approach is proposed to design multiple test conditions for shot cut detection, which are organized into a multiple phase decision tree for abrupt cut detection and a finite state machine for dissolve detection. In comparison with existing approaches, our algorithm is characterized with two categories of content difference indicators and testing. While the first category indicates the content changes that are directly used for shot cut detection, the second category indicates the contexts under which the content change occurs. As a result, indications of frame differences are tested with context awareness to make the detection of shot cuts adaptive to both content and context changes. Evaluations announced by TRECVID 2007 indicate that our proposed algorithm achieved comparable performance to those using machine learning approaches, yet using a simpler feature set and straightforward design strategies. This has validated the effectiveness of modelling of content-aware indicators for decision making, which also provides a good alternative to conventional approaches in this topic.
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References
Available online, http://www-nlpir.nist.gov/projects/trecvid/trecvid.data.html
Bescos J, Cisneros G, Martinez JM et al (2005) A unified model for techniques on video-shot transition detection. IEEE Trans Multimedia 7(2):293–307
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
Cao J, Cai A (2007) A robust shot transition detection method based on support vector machine in compressed domain. Pattern Recogn Lett 28(12):1534–1540
Cooper M, Liu T, Rieffel E (2007) Video segmentation via temporal pattern classification. IEEE Trans Multimedia 9, no.3:610–618
Cotsaces C, Nikolaidis N, Pitas I (2006) Video shot detection and condensed representation. A review. IEEE Signal Process Mag 23(2):28–37
Fang H, Jiang J, Feng Y (2006) A fuzzy logic approach for detection of video shot boundaries. Pattern Recogn 39(11):2092–2100
Ford RM, Robson C, Temple D, Gerlach M (2000) Metrics for shot boundary detection in digital video sequences. Multimedia Syst 8(1):37–46
Gargi U, Kasturi R, Strayer SH (2000) Performance characterization of video-shot-change detection methods. IEEE Trans Circuits Syst Video Technol 10(1):1–13
Grana C, Cucchiara R (2007) Linear transition detection as a unified shot detection approach. IEEE Trans Circuits Syst Video Technol 17(4):483–489
Hanjalic A (2002) Shot boundary detection: unraveled and resolved? IEEE Trans Circuits Syst Video Technol 12(2):90–105
Hoey J, Little JJ (2007) Value-directed human behavior analysis from video using partially observable Markov decision processes. IEEE Trans Pattern Anal Mach Intell 29(7):1118–1132
Lefèvre S, Vincent N (2007) Efficient and robust shot change detection. J Real-Time Image Proc 2(1):23–34
Li S, Lee M-C (2007) An efficient spatiotemporal attention model and its application to shot matching. IEEE Trans Circuits Syst Video Technol 17(10):1383–1387
Li D, Sethi IK (1999) MDC: a software tool for developing MPEG applications. Proc. IEEE International Conference on Multimedia Computing and Systems (ICMCS‘99), vol 1, pp 445–450
Lienhart R (2001) Reliable transition detection in videos: a survey and practitioner’s guide. Int J Image Graph 1(3):469–486
Liu Z, Gibbon D, Zavesky E, Shahraray B, Haffner P. AT&T research at TRECVID 2006. Available online, http://www-nlpir.nist.gov/projects/tvpubs/tv.pubs.org.html#2006
Liu TY, Lo KT, Zhang X-D, Feng J (2004) A new cut detection algorithm with constant false-alarm ratio for video segmentation. J Vis Comm Image Represent 15(2):132–144
Matsumoto K, Sugano M et al. Shot boundary detection and low-Level feature extraction experiments for TRECVID 2005. Available online, http://www-nlpir.nist.gov/projects/tvpubs/tv.pubs.org.html#2005
Meng J, Yuan Y, Chang S-F (1995) Scene change detection in a MPEG compressed video sequence. Proc SPIE 2419:14–25
Patel K, Smith BC, Rowe LA. Performance of a software MPEG video decoder. Prof. 1st ACM Int. Conf. Multimedia, pp 75–82, August 1993
Pei S-C, Chou Y-Z (1999) Efficient MPEG compressed video analysis using macroblock type information. IEEE Trans Multimedia 1(4):321–333
Porter S, Mirmehdi M, Thosmas B (2003) Temporal video segmentation and classification of edit effects. Image Vis Comput 21(13–14):1097–1106
Qiu K, Jiang J, Xiao G (2006) An edge based content descriptor for content based image and video indexing. Lect Notes Comput Sci 4141(1):673–684
Rasheed Z, Shah M (2005) Detection and representation of scenes in videos. IEEE Trans Multimedia 7(6):1097–1105
Ren J, Jiang J, Chen J (2009) Shot boundary detection in MPEG videos using local and global indicators. IEEE Trans Circuits Syst Video Technol 19(8):1234–1238
Urhan O, Gullu MK, Erturk S (2006) Modified phase-correlation based robust hard-cut detection with application to archive film. IEEE Trans Circuits Syst Video Technol 16(6):753–770
Yang K-C, Guest CC, El-Maleh K, Das PK (2007) Perceptual temporal quality metric for compressed video. IEEE Trans Multimedia 9(7):1528–1535
Yeo BL, Liu B (1995) Rapid scene analysis on compressed video. IEEE Trans Circuits Syst Video Technol 5(6):533–544
Yuan J, Wang H, Xiao L, Zheng W, Li J, Lin F, Zhang B (2007) A formal study of shot boundary detection. IEEE Trans Circuits Syst Video Technol 17(2):168–186
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The authors wish to acknowledge the financial support from EU IST FP-7 Research Programme under the STREP project HERMES (Contract No. IST-216709).
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Chen, J., Ren, J. & Jiang, J. Modelling of content-aware indicators for effective determination of shot boundaries in compressed MPEG videos. Multimed Tools Appl 54, 219–239 (2011). https://doi.org/10.1007/s11042-010-0518-y
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DOI: https://doi.org/10.1007/s11042-010-0518-y