Abstract
We present a clustering approach for video summarization and browsing based on the Growing Cell Structures (GCS) neural algorithms and MPEG-7 video descriptors. Each I frame is represented as a feature vector of MPEG-7 descriptors. These vectors are clustered using GCS to select one or more keyframes for each shot. The extracted keyframes are then grouped together by TreeGCS to form a hierarchical view of the video for efficient browsing. We evaluate the effectiveness of different combinations of MPEG-7 descriptors and also compare them with the performance of color histograms.
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Saberi, M.D., Carrato, S., Koprinska, I., Clark, J. (2005). Estimation of the Hierarchical Structure of a Video Sequence Using MPEG-7 Descriptors and GCS. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552451_2
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DOI: https://doi.org/10.1007/11552451_2
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