Abstract
In the entire content-based video technologies, video shot boundary detection (VSBD) is a crucial task. VSBD is used to segment the video into shots. In this paper, we propose a VSBD technique which identifies the abrupt (cut) gradual transitions in video sequence. In our technique, we first extract the multiple feature vectors from video sequence using discrete Haar transform (DHT) for N = 4. The similarity between successive video frames is measured using extracted features, and a continuous signal is computed. To identify shot transition, procedure-based shot detection algorithm is applied on continuous signal. The proposed technique is evaluated on TRECVID test collection videos. The experimental results show that the proposed technique performs better than the existing method in identifying cuts and gradual transitions.
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References
G. Lakshmi Priya, S. Domnic, Walsh-Hadamard transform Kernel-based feature vector for shot boundary detection. IEEE Trans. Image Process. 23(12), 5187–5197 (2014)
Z.-M. Lu, S. Yong, Fast video shot boundary detection based on SVD and pattern matching. IEEE Trans. Image Process. 22(12), 5136–5145 (2013)
G.L. Priya, S. Domnic, Video cut detection using block based histogram differences in RGB color space, in International Conference on Signal and Image Processing, pp. 29–33 (2010)
D. Asha, Y. Madhavee Latha, V.S.K. Reddy, Content based video retrieval system using multiple features. Int. J. Pure Appl. Math. (IJPAM) 118(14), 287–294 (2018)
J. Lankinen, J.K. Kamarainen, Video shot boundary detection using visual bag-of-words, in Proceedings of International Conference Computing Vision Theory Application (VISAPP), pp. 788–791 (2013)
Lian, Automatic video temporal segmentation based on multiple features. Soft. Comput. 15(3), 469–482 (2011)
S.D. Thepade, N. Yadav, Novel efficient content based video retrieval method using Cosine-Haar hybrid wavelet transform with energy compaction, in International Conference Computing Communication Control and Automation, pp 615–619 (2015)
D.F. Walnut, The discrete Haar transform, in An Introduction to Wavelet Analysis. Applied and Numerical Harmonic Analysis (Birkhäuser, Boston, MA.S., 2004)
TREC Video Retrieval Test Collection [online] (2001), Available on website: http://trevid.nist.gov/ and www.open-video.org
Google video.URL http://video.google.com/
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Asha, D., Madhavee Latha, Y. (2019). Content-Based Video Shot Boundary Detection Using Multiple Haar Transform Features. In: Wang, J., Reddy, G., Prasad, V., Reddy, V. (eds) Soft Computing and Signal Processing . Advances in Intelligent Systems and Computing, vol 900. Springer, Singapore. https://doi.org/10.1007/978-981-13-3600-3_67
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DOI: https://doi.org/10.1007/978-981-13-3600-3_67
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