Abstract
Processing of video data is embossed very importantly in ubiquitous environment. This paper proposes a Scene Change Detection method using the local decision tree and clustering. The local decision tree detects cluster boundaries wherein local scenes occur, in such a way as to compare time similarity distributions among the difference values between detected scenes and their adjacent frames, and group an unbroken sequence of frames with similarities in difference value into a cluster unit. In other words, the local decision tree method is used to detect local scenes from a cluster segmentation unit.
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Seong-Yoon, S., Jong-Chan, L., Seong-Eun, B., Oh-Hyong, K., Jung-Hoon, S., Yang-Won, R. (2008). Scene Change Detection Using a Local Detection Tree and Clustering in Ubiquitous Environment. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2008. ICCSA 2008. Lecture Notes in Computer Science, vol 5073. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69848-7_31
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DOI: https://doi.org/10.1007/978-3-540-69848-7_31
Publisher Name: Springer, Berlin, Heidelberg
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