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Title
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Recognizing actions in high-resolution low-framerate videos : a feasibility study in the construction sector
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Author
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Abstract
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| 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. |
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Language
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English
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Source (book)
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Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 27-29 February, 2024, Rome, Italy
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Publication
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SciTePress
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2024
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ISBN
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978-989-758-679-8
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DOI
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10.5220/0012423900003660
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Volume/pages
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p. 593-600
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Full text (Publisher's DOI)
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Full text (open access)
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