Abstract
The shot is basic physical unit of video sequence, which is a collection of several consecutive frames in time and space that is captured by a camera. Shot boundary detection is the structural basis of video retrieval, the performance of detection algorithm will directly affect the efficiency of video retrieval. By describing and analyzing advantages and disadvantages of existing algorithms, this paper proposes a shot detection algorithm of self-adaptive dual thresholds based on multi-feature fusion. Firstly, frame difference is calculated by combining HSV color feature and LBP texture feature in the image that is non-uniformly divided into several blocks. Secondly, frame difference is compared with two self-adaptive thresholds to detect shot boundary. Finally, video is segmented some independent shots. Experiment analysis shows that this algorithm can’t only extract features that reflect main contents of video images, but also effectively detect abrupt shots and gradual shots. It reduces the number of false detection and miss detection, therefore, it has higher recall and precision than existing shot boundary detection algorithms. To a certain extent, this algorithm improves the efficiency of shot boundary detection.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Wang, S., Jia, K., Wang, C., Liu, W.: Abrupt cut detection and key frame extraction based on motion information. Comput. Eng. 16, 5–8 (2012)
Liu, G., Wen, X., Zheng, W., et al.: Shot boundary detection and keyframe extraction based on scale invariant feature transform. In: Eigth IEEE/ACIS International Conference on Computer and Information Science, pp. 1126–1130. IEEE Computer Society (2009)
Wei, M.: The Research of the Key Frame Extraction Algorithm of Content-based Video Retrieval. Wuhan Polytechnic University (2010)
Quandong, L.: Content-Based Video Retrieval Research on Shot Detection and Key Frame Extraction. North University of China (2011)
Feng, H., Yuan, X., Wei, M., et al.: A shot boundary detection method based on color space. In: Proceedings of the International Conference on E-Business and E-Government, ICEE 2010, 7–9 May 2010, Guangzhou, China, pp. 1647–1650 (2010)
Quanlei, H.: Research on Content-based Video Shot Segmentation and Retrieval Technology. Shandong University (2009)
Quintyne, K.I., Walsh, L., Coate, L.: A self-adapting dual-threshold method for video shot transition detection. In: 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC 2008, pp. 704–707 IEEE (2008)
Zhao, N., Ning, L., Liu, H.Y.: Content-based cut shot detecting algorithm of news video. J. Jilin Univ. (2009)
Zhang, M.: The Research on Key Frame Selection and Feature Matching Video Retrieval. Beijing University of Posts and Telecommunications (2012)
Ekin, A., Tekalp, A.M.: Automatic soccer video analysis and summarization. IEEE Trans. Image Process. 12(7), 796–807 (2003)
Lu, Z.M., Shi, Y.: Fast video shot boundary detection based on SVD and pattern matching. IEEE Trans. Image Process. 22(12), 5136–5145 (2013). A Publication of the IEEE Signal Processing Society
Miao, P.: Research on Some Technologies Based on Video Retrieval. Nanjing University of Science and Technology (2010)
Liu, X.: Research on Key Frame Extraction Algorithm Based on Multi-feature in Video Retrieval. China University of Mining and Technology (2015)
Zhou, L.: Research of Shot Detection and Key Frame Extraction of Content-based Video Retrieval. Hebei University of Technology (2014)
Tang, J., Xie, L., Yuan, Q., et al.: Shot boundary detection algorithm based on ORB. J. Commun. 11, 187–190 (2013)
Li, D., Jin, L., Yang, W., Fei, M.: Shot boundary detection algorithm based on self-adaptive dual thresholds of accumulative frame. Comput. Sci. 39(6), 258–260+296 (2012)
Acknowledgments
Science and technology project of Shanxi Province in 2013(20130321007-02).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer-Verlag GmbH Germany
About this chapter
Cite this chapter
Lv, J., Bai, H. (2017). Research on Shot Detection Algorithm of Self-adaptive Dual Thresholds Based on Multi-feature Fusion. In: Pan, Z., Cheok, A., Müller, W., Zhang, M. (eds) Transactions on Edutainment XIII. Lecture Notes in Computer Science(), vol 10092. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54395-5_21
Download citation
DOI: https://doi.org/10.1007/978-3-662-54395-5_21
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-54394-8
Online ISBN: 978-3-662-54395-5
eBook Packages: Computer ScienceComputer Science (R0)