Abstract
This paper presents a group of post-processing techniques aimed to on-line adaptive video summary generation based on video analysis curves, named relevance curves obtained by different approaches (e.g., extraction of visual features, semantic features, rate-distortion curves). The developed techniques can be applied to improve the quality of the generated video summaries, control the summaries length and constitute a way to generate summaries with independence of the approach taken to generate the relevance curves that are used as basis for summary generation.
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Valdés, V., Martínez, J.M. (2007). Post-processing Techniques for On-Line Adaptive Video Summarization Based on Relevance Curves. In: Falcidieno, B., Spagnuolo, M., Avrithis, Y., Kompatsiaris, I., Buitelaar, P. (eds) Semantic Multimedia. SAMT 2007. Lecture Notes in Computer Science, vol 4816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77051-0_17
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DOI: https://doi.org/10.1007/978-3-540-77051-0_17
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