Abstract
Automatic video content analysis and retrieval is crucial for dealing with large amounts of video data. While most of the work has been done on local video segmentation, object detection, genre classification, and event detection, little attention has been given to a systematic approach to temporal video boundary segmentation taking into account overall structural properties of the video.
In this chapter we first categorize the types of temporal boundaries in video into micro-, macro-, and mega-boundaries. We generalize the concept of a video boundary to include information about video segments, taking into account the combination of different attributes present in the different modalities. For each category we present a mathematical framework, detection method and experimental results.
With this new unified approach we want to have a framework for an autonomous video content analysis system that would operationally analyze continuous video sources over long periods of time. This is very important for consumer video applications where metadata is unavailable, incomplete or inaccurate.
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Dimitrova, N., Agnihotri, L., Jasinschi, R. (2003). Temporal Video Boundaries. In: Rosenfeld, A., Doermann, D., DeMenthon, D. (eds) Video Mining. The Springer International Series in Video Computing, vol 6. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-6928-9_3
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DOI: https://doi.org/10.1007/978-1-4757-6928-9_3
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