Publication
Title
Recognizing actions in high-resolution low-framerate videos : a feasibility study in the construction sector
Author
Abstract
Action recognition addresses the automated comprehension of human actions within images or video sequences. Its applications extend across critical areas, mediating between visual perception and intelligent decision-making. However, action recognition encounters multifaceted challenges, including limited annotated data, background clutter, and varying illumination conditions. In the context of the construction sector, distinct challenges arise, requiring specialized approaches. This study investigates the applicability of established action recognition methodologies in this dynamic setting. We evaluate both sequence-based (YOWO) and frame-based (YOLOv8) approaches, considering the effect that resolution and frame rate have on performance. Additionally, we explore self-supervised learning techniques to enhance recognition accuracy. Our analysis aims to guide the development of more effective and efficient practical action recognition methods.
Language
English
Source (book)
Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 27-29 February, 2024, Rome, Italy
Publication
SciTePress , 2024
ISBN
978-989-758-679-8
DOI
10.5220/0012423900003660
Volume/pages
p. 593-600
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Record
Identifier
Creation 22.03.2024
Last edited 23.03.2024
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