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Title: A large-scale re-identification analysis in sporting scenarios: the betrayal of reaching a critical point
Authors: Freire Obregón, David Sebastián 
Lorenzo Navarro, José Javier 
Santana Jaria, Oliverio Jesús 
Hernández Sosa, José Daniel 
Castrillón Santana, Modesto Fernando 
UNESCO Clasification: 33 Ciencias tecnológicas
1203 Ciencia de los ordenadores
Keywords: Surveillance
Feature extraction
Task analysis, et al
Issue Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE) 
Conference: IEEE International Joint Conference on Biometrics (IJCB) 
Abstract: Re-identifying participants in ultra-distance running competitions can be daunting due to the extensive distances and constantly changing terrain. To overcome these challenges, computer vision techniques have been developed to analyze runners’ faces, numbers on their bibs, and clothing. However, our study presents a novel gait-based approach for runners’ re-identification (re-ID) by leveraging various pre-trained human action recognition (HAR) models and loss functions. Our results show that this approach provides promising results for re-identifying runners in ultradistance competitions. Furthermore, we investigate the significance of distinct human body movements when athletes are approaching their endurance limits and their potential impact on re-ID accuracy. Our study examines how the recognition of a runner’s gait is affected by a competition’s critical point (CP), defined as a moment of severe fatigue and the point where the finish line comes into view, just a few kilometers away from this location. We aim to determine how this CP can improve the accuracy of athlete re-ID. Our experimental results demonstrate that gait recognition can be significantly enhanced (up to a 9% increase in mAP) as athletes approach this point. This highlights the potential of utilizing gait recognition in real-world scenarios, such as ultra-distance competitions or long-duration surveillance tasks.
ISBN: 979-8-3503-3726-6
ISSN: 2474-9699
DOI: 10.1109/IJCB57857.2023.10448781
Source: 2023 IEEE International Joint Conference on Biometrics (IJCB), Ljubljana, Slovenia, , p. 1-9, (2023)
Appears in Collections:Actas de congresos
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