Multi-Target Multi-Camera Tracking of Vehicles using Metadata-Aided
Re-ID and Trajectory-Based Camera Link Model
- URL: http://arxiv.org/abs/2105.01213v1
- Date: Mon, 3 May 2021 23:20:37 GMT
- Title: Multi-Target Multi-Camera Tracking of Vehicles using Metadata-Aided
Re-ID and Trajectory-Based Camera Link Model
- Authors: Hung-Min Hsu, Jiarui Cai, Yizhou Wang, Jenq-Neng Hwang, Kwang-Ju Kim
- Abstract summary: We propose a novel framework for multi-target multi-camera tracking of vehicles based on metadata-aided re-identification (MA-ReID) and the trajectory-based camera link model (TCLM)
The proposed method is evaluated on the CityFlow dataset, achieving IDF1 76.77%, which outperforms the state-of-the-art MTMCT methods.
- Score: 32.01329933787149
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In this paper, we propose a novel framework for multi-target multi-camera
tracking (MTMCT) of vehicles based on metadata-aided re-identification
(MA-ReID) and the trajectory-based camera link model (TCLM). Given a video
sequence and the corresponding frame-by-frame vehicle detections, we first
address the isolated tracklets issue from single camera tracking (SCT) by the
proposed traffic-aware single-camera tracking (TSCT). Then, after automatically
constructing the TCLM, we solve MTMCT by the MA-ReID. The TCLM is generated
from camera topological configuration to obtain the spatial and temporal
information to improve the performance of MTMCT by reducing the candidate
search of ReID. We also use the temporal attention model to create more
discriminative embeddings of trajectories from each camera to achieve robust
distance measures for vehicle ReID. Moreover, we train a metadata classifier
for MTMCT to obtain the metadata feature, which is concatenated with the
temporal attention based embeddings. Finally, the TCLM and hierarchical
clustering are jointly applied for global ID assignment. The proposed method is
evaluated on the CityFlow dataset, achieving IDF1 76.77%, which outperforms the
state-of-the-art MTMCT methods.
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