Abstract
We present a shot segmentation method based on the representation of visual contents in video using a coupled Markov chains approach. This representation allows us to combine different image features and to keep information about all the images since the beginning of the shot, instead of simply comparing adjacent frames. We also define an adaptative detection threshold that depends on the distance measures that are obtained, instead of trying to find a fixed threshold. Results show that the combination of color and motion image features in the same representation provides a more robust detection of shot boundaries than using each feature separately.
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Sánchez, J.M., Binefa, X. (2003). Shot Segmentation Using a~Coupled Markov Chains Representation of Video Contents. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_104
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DOI: https://doi.org/10.1007/978-3-540-44871-6_104
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