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Cross-Video Pedestrian Tracking Algorithm with a Coordinate Constraint

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Publicado en:Sensors vol. 24, no. 3 (2024), p. 779
Autor principal: Huang, Cheng
Otros Autores: Li, Weihong, Yang, Guang, Yan, Jiachen, Zhou, Baoding, Li, Yujun
Publicado:
MDPI AG
Materias:
Accuracy
Cameras
Algorithms
Security management
Surveillance
Localization
Video recordings
Pedestrians
Calibration
Neural networks
Acceso en línea:Citation/Abstract
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Resumen:Pedestrian tracking in surveillance videos is crucial and challenging for precise personnel management. Due to the limited coverage of a single video, the integration of multiple surveillance videos is necessary in practical applications. In the realm of pedestrian management using multiple surveillance videos, continuous pedestrian tracking is quite important. However, prevailing cross-video pedestrian matching methods mainly rely on the appearance features of pedestrians, resulting in low matching accuracy and poor tracking robustness. To address these shortcomings, this paper presents a cross-video pedestrian tracking algorithm, which introduces spatial information. The proposed algorithm introduces the coordinate features of pedestrians in different videos and a linear weighting strategy focusing on the overlapping view of the tracking process. The experimental results show that, compared to traditional methods, the method in this paper improves the success rate of target pedestrian matching and enhances the robustness of continuous pedestrian tracking. This study provides a viable reference for pedestrian tracking and crowd management in video applications.
ISSN:1424-8220
DOI:10.3390/s24030779
Fuente:Health & Medical Collection