Abstract
In this paper, a video segmentation algorithm based on Hidden Markov Model classifier with multimodal feature is proposed. By using Hidden Markov Model classifier with both audio and visual features, erroneous shot boundary detection and over-segmentation were avoided compared with conventional algorithms. The experimental results show that the propose method is effective in shot detection.
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© 2004 Springer-Verlag Berlin Heidelberg
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Bae, T.M., Jin, S.H., Ro, Y.M. (2004). Video Segmentation Using Hidden Markov Model with Multimodal Features. In: Enser, P., Kompatsiaris, Y., O’Connor, N.E., Smeaton, A.F., Smeulders, A.W.M. (eds) Image and Video Retrieval. CIVR 2004. Lecture Notes in Computer Science, vol 3115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27814-6_48
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DOI: https://doi.org/10.1007/978-3-540-27814-6_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22539-3
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