Abstract
Past editions of the annual Video Browser Showdown (VBS) event have brought forward many tools targeting a diverse amount of techniques for interactive video search, among which sketch-based search showed promising results. Aiming at exploring this direction further, we present a custom approach for tackling the problem of finding similarities in the TRECVID IACC.3 dataset via hand-drawn pictures using color compositions together with contour matching. The proposed methodology is integrated into the established Collaborative Feature Maps (CFM) system, which has first been utilized in the VBS 2017 challenge.
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Notes
- 1.
VBS has first been organized in 2012 [8].
- 2.
The current IACC.3 dataset contains 600 h of video.
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Leibetseder, A., Kletz, S., Schoeffmann, K. (2018). Sketch-Based Similarity Search for Collaborative Feature Maps. In: Schoeffmann, K., et al. MultiMedia Modeling. MMM 2018. Lecture Notes in Computer Science(), vol 10705. Springer, Cham. https://doi.org/10.1007/978-3-319-73600-6_45
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DOI: https://doi.org/10.1007/978-3-319-73600-6_45
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