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Scene Detection in Videos Using Shot Clustering and Symbolic Sequence Segmentation | IEEE Conference Publication | IEEE Xplore

Scene Detection in Videos Using Shot Clustering and Symbolic Sequence Segmentation


Abstract:

Video indexing requires the efficient segmentation of the video into scenes. In the method we propose, the video is first segmented into shots and key-frames are extracte...Show More

Abstract:

Video indexing requires the efficient segmentation of the video into scenes. In the method we propose, the video is first segmented into shots and key-frames are extracted using the global k-means clustering algorithm that represent each shot. Then an improved spectral clustering method is applied to cluster the shots into groups based on visual similarity and a label is assigned to each shot according to the group that it belongs to. Next, a method for segmenting the sequence of shot labels is applied, providing the final scene segmentation result. Numerical experiments indicate that the method we propose correctly detects most of the scene boundaries while preserving a good trade off between recall and precision.
Date of Conference: 01-03 October 2007
Date Added to IEEE Xplore: 02 January 2008
ISBN Information:
Conference Location: Chania, Greece

References

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