A Framework for Effective Known-item Search in Video

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10401600" target="_blank" >RIV/00216208:11320/19:10401600 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1145/3343031.3351046" target="_blank" >https://doi.org/10.1145/3343031.3351046</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3343031.3351046" target="_blank" >10.1145/3343031.3351046</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Framework for Effective Known-item Search in Video

Popis výsledku v původním jazyce

Searching for one particular scene in a large video collection (known-item search) represents a challenging task for video retrieval systems. According to the recent results reached at evaluation campaigns, even respected approaches based on machine learning do not help to solve the task easily in many cases. Hence, in addition to effective automatic multimedia annotation and embedding, interactive search is recommended as well. This paper presents a comprehensive description of an interactive video retrieval framework VIRET that successfully participated at several recent evaluation campaigns. Utilized video analysis, feature extraction and retrieval models are detailed as well as several experiments evaluating effectiveness of selected system components. The results of the prototype at the Video Browser Showdown 2019 are highlighted in connection with an analysis of collected query logs. We conclude that the framework comprise a set of effective and efficient models for most of the evaluated known-item search tasks in 1000 hours of video and could serve as a baseline reference approach. The analysis also reveals that the result presentation interface needs improvements for better performance of future VIRET prototypes.

Název v anglickém jazyce

A Framework for Effective Known-item Search in Video

Popis výsledku anglicky

Searching for one particular scene in a large video collection (known-item search) represents a challenging task for video retrieval systems. According to the recent results reached at evaluation campaigns, even respected approaches based on machine learning do not help to solve the task easily in many cases. Hence, in addition to effective automatic multimedia annotation and embedding, interactive search is recommended as well. This paper presents a comprehensive description of an interactive video retrieval framework VIRET that successfully participated at several recent evaluation campaigns. Utilized video analysis, feature extraction and retrieval models are detailed as well as several experiments evaluating effectiveness of selected system components. The results of the prototype at the Video Browser Showdown 2019 are highlighted in connection with an analysis of collected query logs. We conclude that the framework comprise a set of effective and efficient models for most of the evaluated known-item search tasks in 1000 hours of video and could serve as a baseline reference approach. The analysis also reveals that the result presentation interface needs improvements for better performance of future VIRET prototypes.

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/GJ19-22071Y" target="_blank" >GJ19-22071Y: Flexibilní modely pro hledání známé scény v rozsáhlých kolekcích videa</a><br>

Návaznosti

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

Rok uplatnění

2019

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 27th ACM International Conference on Multimedia

ISBN

978-1-4503-6889-6

ISSN

—

e-ISSN

—

Počet stran výsledku

9

Strana od-do

1777-1785

Název nakladatele

ACM

Místo vydání

New York, NY, USA

Místo konání akce

Nice, France

Datum konání akce

21. 10. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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