Exquisitor at the Video Browser Showdown 2020

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F20%3A00344442" target="_blank" >RIV/68407700:21730/20:00344442 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-030-37734-2_72" target="_blank" >https://doi.org/10.1007/978-3-030-37734-2_72</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-37734-2_72" target="_blank" >10.1007/978-3-030-37734-2_72</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Exquisitor at the Video Browser Showdown 2020

Popis výsledku v původním jazyce

When browsing large video collections, human-in-the-loop systems are essential. The system should understand the semantic information need of the user and interactively help formulate queries to satisfy that information need based on data-driven methods. Full synergy between the interacting user and the system can only be obtained when the system learns from the user interactions while providing immediate response. Doing so with dynamically changing information needs for large scale multimodal collections is a challenging task. To push the boundary of current methods, we propose to apply the state of the art in interactive multimodal learning to the complex multimodal information needs posed by the Video Browser Showdown (VBS). To that end we adapt the Exquisitor system, a highly scalable interactive learning system. Exquisitor combines semantic features extracted from visual content and text to suggest relevant media items to the user, based on user relevance feedback on previously suggested items. In this paper, we briefly describe the Exquisitor system, and its first incarnation as a VBS entrant.

Název v anglickém jazyce

Exquisitor at the Video Browser Showdown 2020

Popis výsledku anglicky

When browsing large video collections, human-in-the-loop systems are essential. The system should understand the semantic information need of the user and interactively help formulate queries to satisfy that information need based on data-driven methods. Full synergy between the interacting user and the system can only be obtained when the system learns from the user interactions while providing immediate response. Doing so with dynamically changing information needs for large scale multimodal collections is a challenging task. To push the boundary of current methods, we propose to apply the state of the art in interactive multimodal learning to the complex multimodal information needs posed by the Video Browser Showdown (VBS). To that end we adapt the Exquisitor system, a highly scalable interactive learning system. Exquisitor combines semantic features extracted from visual content and text to suggest relevant media items to the user, based on user relevance feedback on previously suggested items. In this paper, we briefly describe the Exquisitor system, and its first incarnation as a VBS entrant.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF15_003%2F0000470" target="_blank" >EF15_003/0000470: Robotika pro Průmysl 4.0</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

MultiMedia Modeling

ISBN

978-3-030-37733-5

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

7

Strana od-do

796-802

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Daejeon

Datum konání akce

5. 1. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000611566100072