상세정보
학술지
Multi-Target Multi-Camera Tracking of Vehicles using Metadata-Aided Re-ID and Trajectory-Based Camera Link Model
- 저자
- Hung-Min Hsu, Jiarui Cai, Yizhou Wang, Jenq-Neng Hwang, 김광주
- 발행일
- 202105
- 출처
- IEEE Transactions on Image Processing, v.30, pp.5198-5210
- ISSN
- 1057-7149
- 출판사
- IEEE
- 협약과제
- 20ZD1100, 대경권 지역산업 기반 ICT 융합기술 고도화 지원사업, 문기영
- 초록
- 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.
- KSP 제안 키워드
- Attention model, Hierarchical Clustering, Multi-Target, Re-Identification, Robust distance, Spatial and temporal, Traffic-Aware, camera link model, distance measure, multi-camera tracking, single camera