Action recognition in law enforcement: A novel dataset from body worn cameras

Hans, Sameer; Dugelay, Jean-Luc; Isa, Mohd Rizal Mohd; Khairuddin, Mohammad Adib
ICPRAM 2025, 14th International Conference on Pattern Recognition Applications and Methods, 23-25 February 2025, Porto, Portugal

Over the past decade, there has been a notable increase in the integration of body worn cameras (BWCs) in many professional settings, particularly in law enforcement. BWCs serve as valuable tools for enhancing transparency, accountability, and security by providing real-time, first-person perspective recordings of interactions and events. These devices capture vast amounts of video data, which can offer critical insights into
the behaviors and actions of individuals in diverse scenarios. This paper aims to explore the intersection of BWCs and action recognition methodologies. We introduce FALEBaction: a multimodal dataset for action recognition using body worn cameras, with actions relevant to BWCs and law enforcement usage. We investigate the methodologies employed in extracting meaningful patterns from BWC footage, the effectiveness of deep learning models in recognizing similar actions, and the potential applications and implications of these advancements. By focusing on actions relevant to law enforcement scenarios, we ensure that our dataset meets the practical needs of the authorities and researchers aiming to enhance public safety through advanced video analysis technologies. The entire dataset can be obtained upon request from the authors to facilitate further research in this domain.

Type:
Conference
City:
Porto
Date:
2025-02-23
Department:
Digital Security
Eurecom Ref:
8018
Copyright:
© ACM, 2025. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ICPRAM 2025, 14th International Conference on Pattern Recognition Applications and Methods, 23-25 February 2025, Porto, Portugal

PERMALINK : https://www.eurecom.fr/publication/8018