In this paper, a novel method for video content summarization has been proposed by calculating the fractal dimension of frames. Summarization of the video is the first step in automatic video analysis. In this paper, we use the support vector machine (SVM) and the decision - tree to identify the shot boundary and classify them. In order to compute the fractal dimension, the numerical method has been expressed. The results of this implementation were also reported on TRECVID 2006 data collection. The results show that the relative advantage of the method presented in this paper is compared to other articles.
Yarmohammadi, H., Marvi, H., Hassanpour, H. (2019). Application of 2-D fractal dimension in content based video summarization. International Journal of Nonlinear Analysis and Applications, 10(2), 131-140. doi: 10.22075/ijnaa.2019.4180
MLA
Hadi Yarmohammadi; Hossein Marvi; Hamid Hassanpour. "Application of 2-D fractal dimension in content based video summarization". International Journal of Nonlinear Analysis and Applications, 10, 2, 2019, 131-140. doi: 10.22075/ijnaa.2019.4180
HARVARD
Yarmohammadi, H., Marvi, H., Hassanpour, H. (2019). 'Application of 2-D fractal dimension in content based video summarization', International Journal of Nonlinear Analysis and Applications, 10(2), pp. 131-140. doi: 10.22075/ijnaa.2019.4180
VANCOUVER
Yarmohammadi, H., Marvi, H., Hassanpour, H. Application of 2-D fractal dimension in content based video summarization. International Journal of Nonlinear Analysis and Applications, 2019; 10(2): 131-140. doi: 10.22075/ijnaa.2019.4180
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