bibtype M - Monography Chapter
ARLID 0638575
utime 20250918141851.9
mtime 20250903235959.9
DOI 10.1007/978-3-031-88486-3_1
title (primary) (eng) Automated Actor Recognition in Video Content
specification
page_count 20 s.
book_pages 302
media_type P
serial
ARLID cav_un_epca*0638914
ISBN 978-3-031-88485-6
title Data Science in Applications : Towards AI-Driven Approaches
page_num 3-22
publisher
place Cham
name Springer
year 2025
editor
name1 Dzemyda
name2 G.
editor
name1 Bernatavičienė
name2 J.
editor
name1 Kacprzyk
name2 J.
keyword Actor recognition
keyword Face detection
keyword Video analysis
keyword Screen time calculation
author (primary)
ARLID cav_un_auth*0379363
name1 Kerepecký
name2 Tomáš
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept (eng) Department of Image Processing
department (cz) ZOI
department (eng) ZOI
full_dept Department of Image Processing
country CZ
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101209
name1 Šroubek
name2 Filip
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101238
name1 Zitová
name2 Barbara
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101087
name1 Flusser
name2 Jan
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url https://library.utia.cas.cz/separaty/2025/ZOI/kerepecky-0638575.pdf
source
url https://link.springer.com/book/10.1007/978-3-031-88486-3
cas_special
project
project_id GA24-10069S
agency GA ČR
country CZ
ARLID cav_un_auth*0472834
abstract (eng) This chapter presents an AI pipeline designed for automated recognition and analysis of actors in video content. The pipeline incorporates advanced methodologies in computer vision, allowing for a comprehensive analysis of actor presence and screen time across various video formats, such as movies, television shows, and surveillance footage. To evaluate the pipeline performance, we conducted extensive experiments using a carefully annotated test videos from a Czech TV show available for download. The evaluation criteria focus on precision, recall, mean absolute error metrics for actor recognition and screen time calculation under varying conditions. Additionally, we discuss challenges encountered during the pipeline development and consider its potential implications for the future of AI-driven content analysis and security surveillance.
RIV IN
FORD0 10000
FORD1 10200
FORD2 10201
reportyear 2026
num_of_auth 4
inst_support RVO:67985556
permalink https://hdl.handle.net/11104/0369467
confidential S
arlyear 2025
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU63 cav_un_epca*0638914 Data Science in Applications : Towards AI-Driven Approaches Springer 2025 Cham 3 22 978-3-031-88485-6 Studies in Computational Intelligence
mrcbU67 Dzemyda G. 340
mrcbU67 Bernatavičienė J. 340
mrcbU67 Kacprzyk J. 340