Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

1-2019

Abstract

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 k-means and self-organizing-map and used for visualization. Also, the relevance feedback module which relies on real-time supportvector-machine classification becomes unfeasible with the large dataset provided in VBS 2019 and has been replaced by a browsing module with pre-calculated nearest neighbors.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.

Keywords

Video browser showdown, Video retrieval, Video visualization

Discipline

Data Storage Systems | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

MultiMedia Modeling: 25th International Conference, MMM 2019, Thessaloniki, Greece, January 8-11: Proceedings

Volume

11296

First Page

609

Last Page

615

ISBN

9783030057152

Identifier

10.1007/978-3-030-05716-9_54

Publisher

Springer

City or Country

Cham

Additional URL

https://doi.org/10.1007%2F978-3-030-05716-9_54

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