DVSMOT: Dual View Sharing for Enhanced Multi-Object Tracking and ID Switch Reduction
Heon Jun Shin, Jun-Yung Oh, Woo-Seok Choi, J.H. Cho, Yeonseok Lee, Tae-Kyung Kim · 2025
Multiple Object Tracking (MOT) has applications across many fields, yet occlusion-related issues continue to impact its effectiveness. These occlusions lead to information loss, reducing model performance and causing re-identification errors. In response, this study introduces a Dual View Sharing Multi Object Tracking (DVSMOT) method. Results show that this approach minimizes information loss due to occlusion, improves re-identification accuracy, and enhances tracking precision in experimental trials compared to traditional methods.