Bài báo: “An Approach for Real-Time Object Tracking Integration with Adaptive Occlusion Handling on the Elderly-Care Robot”
Link bài báo: https://link.springer.com/.../10.1007/978-981-96-7514-2_39
Sinh viên thực hiện:
. Lê Thị Phương Nhi - KTMT2021
. Võ Đông Thành - KTMT2021
Giảng viên hướng dẫn:
. TS. Nguyễn Minh Sơn
. KS. Thân Thế Tùng
Tóm tắt:
Object tracking is crucial in computer vision, particularly in robotics, but visual object tracking (VOT) faces significant challenges, with occlusion being the most critical. Occlusion disrupts tracking accuracy and poses difficulties when integrating VOT algorithms into embedded robotic systems due to computational and real-time constraints. To address this, we propose a robust method tailored for resource-limited systems, combining the Kernelized Correlation Filter (KCF) and Kalman Filter (KF). By leveraging the Average Peak-to-Correlation Energy (APCE) index, our method detects occlusion, dynamically adjusts the model’s learning rate, and improves performance under challenging conditions. Experimental results on the OTB100 benchmark highlight our tracker’s effectiveness in handling occlusion, achieving a success rate of 0.602. This demonstrates the method’s robustness under challenging conditions while maintaining real-time processing at 30 FPS (Frame per Second) on Jetson Nano, making it an ideal solution for embedded robotic systems.
"Chúng em xin gửi lời tri ân sâu sắc đến TS. Nguyễn Minh Sơn và KS. Thân Thế Tùng đã luôn đồng hành, hỗ trợ và định hướng nhóm trong suốt quá trình thực hiện đề tài. Những định hướng quý báu, góp ý chuyên môn sâu sắc cùng sự tận tâm hướng dẫn của quý thầy chính là chìa khóa giúp nhóm chúng em hoàn thành tốt nghiên cứu này. Việc được ghi nhận tại hội nghị lần này là một cột mốc ý nghĩa, góp phần củng cố niềm tin và động lực trên con đường học tập và nghiên cứu của chúng em."
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Thông tin chi tiết: https://www.facebook.com/share/p/1CiUkaJDTc/
