STAR: Screen Time and Actor Recognition in Video Content
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00602283" target="_blank" >RIV/67985556:_____/25:00602283 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-031-85187-2_17" target="_blank" >http://dx.doi.org/10.1007/978-3-031-85187-2_17</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-85187-2_17" target="_blank" >10.1007/978-3-031-85187-2_17</a>
Alternative languages
Result language
angličtina
Original language name
STAR: Screen Time and Actor Recognition in Video Content
Original language description
Accurately measuring the duration of actors' presence in videos is a challenging task that goes beyond actor recognition. We propose the STAR pipeline, the new model designed to analyze the time performers appear on screen across diverse video content, including movies and TV shows. The proposed model has been successfully deployed and tested by the Czech TV infrastructure provider. Our pipeline uses machine learning techniques for shot detection, face detection, tracking, recognition, and introduces a novel shot-based method for calculating screen time. We present extensive experiments proving the robustness and real-time performance of our approach. Alongside the pipeline, we introduce the STAR dataset to address the need for high-quality benchmarks in evaluating screen time models, now available for download.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20206 - Computer hardware and architecture
Result continuities
Project
<a href="/en/project/GA24-10069S" target="_blank" >GA24-10069S: Hybrid neural network architectures for image recognition</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Pattern Recognition : 46th DAGM German Conference, DAGM GCPR 2024
ISBN
978-3-031-85186-5
ISSN
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e-ISSN
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Number of pages
15
Pages from-to
270-284
Publisher name
Springer
Place of publication
Cham
Event location
Munich
Event date
Sep 10, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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