Abstract
The temporal segmentation of a video into shots is a fundamental prerequisite for video retrieval. There are two types of shot boundaries: abrupt shot changes (“cuts”) and gradual transitions. Several high-quality algorithms have been proposed for detecting cuts, but the successful detection of gradual transitions remains a surprisingly difficult problem in practice. In this paper, we present an unsupervised approach for detecting gradual transitions. It has several advantages. First, in contrast to alternative approaches, no training stage and hence no training data are required. Second, no thresholds are needed, since the used clustering approach separates classes of gradual transitions and non-transitions automatically and adaptively for each video. Third, it is a generic approach that does not employ a specialized detector for each transition type. Finally, the issue of removing false alarms caused by camera motion is addressed: in contrast to related approaches, it is not only based on low-level features, but on the results of an appropriate algorithm for camera motion estimation. Experimental results show that the proposed approach achieves very good performance on TRECVID shot boundary test data.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bescos, J.: Real-Time Shot Change Detection Over Online MPEG-2 Video. IEEE Transactions on Circuits and Systems for Systems and Video Technology 14(4), 475–484 (2004)
Chandrashekhara, A., Feng, H.M., Chua, T.-S.: Temporal Multi-Resolution Framework for Shot Boundary Detection and Keyframe Extraction. In: Proceedings of the Eleventh Text Retrieval Conference (TREC 2002), pp. 492–496 (2002), http://trec.nist.gov//pubs/trec11/index.track.html#video
Chua, T.-S., Kankanhalli, M., Lin, Y.: A General Framework for Video Segmentation Based on Temporal Multi-Resolution Analysis. In: Proc. of International Workshop on Advanced Image Technology, Fujisawa, Japan, pp. 119–124 (2000)
Chua, T.-S., Feng, H.M., Anantharamu, C.: An Unified Framework for Shot Boundary Detection via Active Learning. In: Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing 2003, Hong Kong, Band II, pp. 845–848. IEEE Press, Los Alamitos (2003)
Ewerth, R., Freisleben, B.: Video Cut Detection without Thresholds. In: Proc. of 11th Int’l Workshop on Signals, Systems and Image Processing, Poznan, Poland, pp. 227–230 (2004)
Ewerth, R., Schwalb, M., Tessmann, P., Freisleben, B.: Estimation of Arbitrary Camera Motion in MPEG Videos. In: Proceedings of the 17th International Conference on Pattern Recognition, Cambridge, UK, vol. I, pp. 512–515. IEEE Press, Los Alamitos (2004)
Ewerth, R.: Robust Video Content Analysis via Transductive Learning Methods. Doctoral thesis (2008), http://archiv.ub.uni-marburg.de/diss/z2008/0478/
Hanjalic, A.: Shot Boundary Detection: Unraveled and Resolved? IEEE Transactions on Circuits and Systems for Video Technology 12, 533–544 (2002)
Lienhart, R.: Comparison of Automatic Shot Boundary Detection Algorithms. In: Image and Video Processing VII 1999, SPIE Proc., vol. 3656(29), pp. 290–301.a (1999)
Lienhart, R.: Reliable Transition Detection in Videos: A Survey and Practitioner’s Guide. International Journal of Image and Graphics 3, 469–486 (2001)
Liu, Z., Zavesky, E., Gibbon, D., Shahraray, B., Haffner, P.: AT&T Research at TRECVID 2007. In: TREC Video Retrieval Online Proceedings (2007), http://www-nlpir.nist.gov/projects/tvpubs/tv7.papers/att.pdf (April 2, 2009)
TRECVID: TREC Video Retrieval Evaluation (March 27, 2009), http://www-nlpir.nist.gov/projects/t01v
Petersohn, C.: Wipe Shot Boundary Determination. In: Proceedings of IS&T/SPIE Electronic Imaging 2005, Storage and Retrieval Methods and Applications for Multimedia, San Jose, CA, USA, pp. 337–346 (2005)
Smeaton, A., Over, P.: TRECVID-2007: Shot Boundary Detection Task Summary (2007), http://www-nlpir.nist.gov/projects/tvpubs/tv7.slides/tv7.sb.slides.pdf (March 27, 2009)
Smeaton, A., Over, P., Doherty, A.: Video Shot Boundary Detection: Seven Years of TRECVid Activity. In: Computer Vision and Image Understanding (in press, 2009) (accepted manuscript) (March 26, 2009), ISSN 1077-3142, dio: 10.1016/j.cviu.2009.03.011 (2009)
Truong, B.T., Dorai, C., Venkatesh, S.: New Enhancements to Cut, Fade, and Dissolve Detection Processes in Video Segmentation. In: Proc. of ACM Multimedia, pp. 219–227 (2000)
Yeo, B.L., Liu, B.: Rapid Scene Analysis on Compressed Video. IEEE Transactions on Circuits and Systems for Video Technology 5(6), 533–544 (1995)
Yuan, J., Wang, H., Xiao, L., Zheng, W., Li, J., Lin, F., Zhang, B.: A Formal Study of Shot Boundary Detection. IEEE Transaction on Circuits and Systems for Video Technology 17(2), 168–186 (2007)
Yuan, J., Guo, Z., Lv, L., Wan, W., Zhang, T., Wang, D., Liu, X., Liu, C., Zhu, S., Wang, D., Pang, Y., Ding, N., Liu, Y., Wang, J., Zhang, X., Tie, X., Wang, Z., Wang, H., Xiao, T., Liang, Y., Li, J., Lin, F., Zhang, B., Li, J., Wu, W., Tong, X., Ding, D., Chen, Y., Wang, T., Zhang, Y.: THU and ICRC at TRECVID 2007. In: Online Proc. of TRECVID Conference Series 2007, April 2 (2009), http://www-nlpir.nist.gov/projects/tvpubs/tv.pubs.org.html
Zheng, W., Yuan, J., Wang, H., Lin, F., Zhang, B.: A Novel Shot Boundary Detection Framework. In: Proceedings of the SPIE. Visual Communications and Image Processing, vol. 5960, pp. 410–420 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ewerth, R., Freisleben, B. (2009). Unsupervised Detection of Gradual Video Shot Changes with Motion-Based False Alarm Removal. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, vol 5807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04697-1_24
Download citation
DOI: https://doi.org/10.1007/978-3-642-04697-1_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04696-4
Online ISBN: 978-3-642-04697-1
eBook Packages: Computer ScienceComputer Science (R0)