The KITTI Vision Benchmark Suite

We propose a 3D MOT system based on a cost-
effective stereo camera pair, which includes a 3D
multimodal re-identification (ReID) model capable
of multi-task learning. The ReID model obtains the
multimodal features of objects, including RGB and
point cloud information. We design data
association and trajectory management algorithms.
The data association computes an affinity matrix
for the object feature embeddings and motion
information, while the trajectory management
controls the lifecycle of the trajectories.

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@inproceedings{mao2023stereo3dmot,
title={Stereo3DMOT: Stereo Vision Based 3D
Multi-object Tracking with Multimodal ReID},
author={Mao, Chen and Tan, Chong and Liu, Hong
and Hu, Jingqi and Zheng, Min},
booktitle={Chinese Conference on Pattern
Recognition and Computer Vision (PRCV)},
pages={495--507},
year={2023},
organization={Springer}
}