Published

Deep Learning-Based Robust Multi-Object Tracking via Fusion of mmWave Radar and Camera Sensors

L. Cheng, A. Sengupta, S. Cao

IEEE Transactions on Intelligent Transportation Systems, 2024 , pp. 17218 - 17233

Abstract

A deep learning-based method integrating radar and camera data for multi-object tracking. Employs Bi-directional LSTM with tri-output mechanisms for robustness to noise and occlusion, combined with appearance feature model inspired by FaceNet for consistent tracking across frames.

Citation

L. Cheng, A. Sengupta, S. Cao. "Deep Learning-Based Robust Multi-Object Tracking via Fusion of mmWave Radar and Camera Sensors." IEEE Transactions on Intelligent Transportation Systems: 17218 - 17233, 2024. DOI: 10.1109/TITS.2024.3421339

Related Projects

Object Tracking via Multimodal Sensor System - Deep Learning Approach

Bi-LSTM based robust multi-object tracking via radar-camera fusion

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Details

Year
2024
Published In
IEEE Transactions on Intelligent Transportation Systems
Pages
17218 - 17233
DOI
10.1109/TITS.2024.3421339
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