Multi-modal Fusion-based Person Re-identification of Individuals in Complex Scenes
Person re-identification(ReID)is a critical task in computer vision with numerous practical applications such as video surveillance and personnel tracking.A novel method was proposed to address the challenges of ReID in complex scenarios,including issues like occlusion,changes in viewpoint,and variations in lighting conditions.Multi-modal fusion techniques were utilized to enhance the discriminative capabilities of the ReID model,making it more robust in challenging real-world scenarios.Extensive experiments were conducted on benchmark datasets to demonstrate the effectiveness of the proposed method,achieving state-of-the-art performance.
video surveillancepersonnel trackingperson re-identificationmulti-modal fusionre-identification(ReID)model