Abstract
The VIREO Known-Item Search (KIS) system has joined the Video Browser Showdown (VBS) [1] evaluation benchmark for the first time in year 2017. With experiences learned, the second version of VIREO KIS is presented in this paper. Considering the color-sketch based retrieval, we propose a simple grid-based approach for color query. This method allows the aggregation of color distributions in video frames into a shot representation, and generates the pre-computed rank list for all available queries which reduces computational resources and favors a recommendation module. With focusing on concept based retrieval, we modify our multimedia event detection system at TRECVID 2015 in VIREO KIS 2017. In this year, the concept bank of VIREO KIS has been upgraded to 14K concepts. An adaptive concept selection, combination and expansion mechanism, which assists the user in picking the right concepts and logically combining concepts to form more expressive query, has been developed. In addition, metadata is included for textual query and some interface designs are also revised for providing a flexible view of results to the user.
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Acknowledgment
The work described in this paper was supported by two grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (CityU 11210514, 11250716).
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Nguyen, P.A., Lu, YJ., Zhang, H., Ngo, CW. (2018). Enhanced VIREO KIS at VBS 2018. 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_42
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DOI: https://doi.org/10.1007/978-3-319-73600-6_42
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