Abstract
This paper concentrates on a graph-based multilevel temporal segmentation method for scripted content videos. In each level of the segmentat-ion, a similarity matrix of frame strings, which are series of consecutive video frames, is constructed by using temporal and spatial contents of frame strings. A strength factor is estimated for each frame string by using a priori information of a scripted content. According to the similarity matrix reevaluated from a strength function derived by the strength factors, a weighted undirected graph structure is implemented. The graph is partitioned to clusters, which represent segments of a video. The resulting structure defines a hierarchically segmented video tree. Comparative performance results of different types of scripted content videos are demonstrated.
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Sakarya, U., Telatar, Z. (2007). Graph-Based Multilevel Temporal Segmentation of Scripted Content Videos. In: Escolano, F., Vento, M. (eds) Graph-Based Representations in Pattern Recognition. GbRPR 2007. Lecture Notes in Computer Science, vol 4538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72903-7_16
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DOI: https://doi.org/10.1007/978-3-540-72903-7_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72902-0
Online ISBN: 978-3-540-72903-7
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