0602283 20260226075835.120241204235959.9 105004254609 10.1007/978-3-031-85187-2_17 15 s. P cav_un_epca*0616816978-3-031-85186-5270-284ChamSpringer2025 Screen Time Actor Recognition Video Analysis Computer Vision Machine Learning Star Dataset cav_un_auth*0379363 Kerepecký Tomáš UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101209 Šroubek Filip UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101238 Zitová Barbara UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101087 Flusser Jan UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. https://library.utia.cas.cz/separaty/2025/ZOI/kerepecky-0602283.pdf GA24-10069S GA ČR CZ cav_un_auth*0472834 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. cav_un_auth*0478046 The German Conference on Pattern Recognition (GCPR) 2024 /46./ 20240910 20240913 Munich DE IN 20000 20200 20206 2026 PO RVO:67985556 https://hdl.handle.net/11104/0365906 S 2025 C 105004254609 SCOPUS PUBMED WOS cav_un_epca*0616816 Pattern Recognition : 46th DAGM German Conference, DAGM GCPR 2024 978-3-031-85186-5 270 284 Cham Springer 2025 Lecture Notes in Computer Science 15298