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Bibliografie

Conference Paper (international conference)

STAR: Screen Time and Actor Recognition in Video Content

Kerepecký Tomáš, Šroubek Filip, Zitová Barbara, Flusser Jan

: Pattern Recognition : 46th DAGM German Conference, DAGM GCPR 2024, p. 270-284

: The German Conference on Pattern Recognition (GCPR) 2024 /46./, (Munich, DE, 20240910)

: GA24-10069S, GA ČR

: Screen Time, Actor Recognition, Video Analysis, Computer Vision, Machine Learning, Star Dataset

: 10.1007/978-3-031-85187-2_17

: https://library.utia.cas.cz/separaty/2025/ZOI/kerepecky-0602283.pdf

: https://link.springer.com/chapter/10.1007/978-3-031-85187-2_17

(eng): 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.

: IN

: 20206