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Shot boundary detection is always an important topic in digital video processing. It is the first important task of content-based video retrieval and indexing. In this paper, a new shot boundary detection algorithm is proposed, based on Particle Swarm Optimization Classifier. This method firstly takes the difference curves of U-component histograms as the characteristics of the differences between video frames, and then utilizes a Slide-Window Mean Filter to filter difference curves and a KNN Classifier applying PSO to detect and classify the shot transitions. This method has three advantages that it is more sensitive to gradual transitions each curve graphic with remarkable characteristics corresponds to a shot transition Cuts and Gradual transitions could be detected in a same step. As experiments shown, the performance of this method is superior to the traditional shot boundary detection methods, and this method can achieve high recall and precision rate.-Shot boundary detection is always an important topic in digital video processing. It is the first important task of content-based video retrieval and indexing. In this paper, a new shot boundary detection algorithm is proposed, based on Particle Swarm Optimization Classifier. This method firstly takes the difference curves of U-component histograms as the characteristics of the differences between video frames, and then utilizes a Slide-Window Mean Filter to filter difference curves and a KNN Classifier applying PSO to detect and classify the shot transitions. This method has three advantages that it is more sensitive to gradual transitions each curve graphic with remarkable characteristics corresponds to a shot transition Cuts and Gradual transitions could be detected in a same step. As experiments shown, the performance of this method is superior to the traditional shot boundary detection methods, and this method can achieve high recall and precision rate.
Date : 2025-12-28 Size : 386kb User : saeed
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