Title:
A-SHOT-BOUNDARY-DETECTION-ALGORITHM-BASED-ON
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Description: 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.
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