In this paper, an effective classification approach for action scenes is proposed, which exploits the film grammar used by filmmakers as guideline to extract features, detect and classify action scenes. First, action scenes are detected by analyzing film rhythm of video sequence. Then four important features are extracted to characterize chase and fight scenes. After then the Probability Neural Networks is employed to classify the detected action scenes into fight, chase and uncertain scenes. Experimental results show that the proposed method works well over the real movie videos. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Geng, Y. L., Xu, D., Yuan, J. Z., & Feng, S. H. (2006). Two important action scenes detection based on probability neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3972 LNCS, pp. 448–453). Springer Verlag. https://doi.org/10.1007/11760023_65
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