MMM 2019, 25th International Conference on Multimedia Modeling, January 8-11, 2019, Thessaloniki, Greece
In this paper, the VIREO team video retrieval tool is described in details. As learned from Video Browser Showdown (VBS) 2018, the visualization of video frames is a critical need to improve the browsing effectiveness. Based on this observation, a hierarchical structure that represents the video frame clusters has been built automatically using kmeans and self-organizing-map and used for visualization. Also, the relevance
feedback module which relies on real-time support-vector-machine classification becomes unfeasible with the large dataset provided in VBS 2019 and has been replaced by a browsing module with pre-calculated nearest neighbors. The preliminary user study results on IACC.3 dataset show that these modules are able to improve the retrieval accuracy and efficiency in real-time video search system.
Type:
Conférence
City:
Thessaloniki
Date:
2019-01-08
Department:
Data Science
Eurecom Ref:
5714
Copyright:
© Springer. Personal use of this material is permitted. The definitive version of this paper was published in MMM 2019, 25th International Conference on Multimedia Modeling, January 8-11, 2019, Thessaloniki, Greece and is available at : http://doi.org/10.1007/978-3-030-05716-9_54
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