Mining Platoon Patterns from Traffic Videos
Summary: Defines relaxed platoon patterns in traffic video that tolerate missing cameras and nonconsecutive observations, addressing occlusion and identity errors. MaxGrowth enumerates cluster-sequence candidates without verification or false positives, with pruning and up to 100× speedups. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Yijun Bei (Zhejiang University)
- 2. Teng Ma (Zhejiang University)
- 3. Dongxiang Zhang (State Key Laboratory of Blockchain and Data Security; Zhejiang University)
- 4. Sai Wu (Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security)
- 5. Kian-Lee Tan (National University of Singapore)
- 6. Gang Chen (Zhejiang University)
BibTeX Citation
@article{bei_vldb25,
title = {{Mining Platoon Patterns from Traffic Videos}},
author = {Bei, Yijun and Ma, Teng and Zhang, Dongxiang and Wu, Sai and Tan, Kian-Lee and Chen, Gang},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {6},
pages = {1839--1851},
doi = {10.14778/3725688.3725710},
url = {https://doi.org/10.14778/3725688.3725710},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,393 | Query-Aware Path Inference from Spatial Videos | 2026 | SIGMOD | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,755 | Swarm: Mining Relaxed Temporal Moving Object Clusters | 2010 | VLDB | 9.8211863e-05 |
| 1,885 | Discovery of Convoys in Trajectory Databases | 2008 | VLDB | 9.5362394e-05 |
| 2,945 | A Unified Approach to Route Planning for Shared Mobility | 2018 | VLDB | 7.9331237e-05 |
| 3,645 | A General and Parallel Platform for Mining Co-Movement Patterns over Large-scale Trajectories | 2017 | VLDB | 7.2293286e-05 |
| 4,475 | UlTraMan: A Unified Platform for Big Trajectory Data Management and Analytics | 2018 | VLDB | 6.6803264e-05 |
| 5,112 | Fast Large-Scale Trajectory Clustering | 2020 | VLDB | 6.3596697e-05 |
| 6,880 | Real-time Distributed Co-Movement Pattern Detection on Streaming Trajectories | 2019 | VLDB | 5.7470112e-05 |
| 7,453 | k/2-hop: Fast Mining of Convoy Patterns With Effective Pruning | 2019 | VLDB | 5.6129682e-05 |
| 9,894 | Co-movement Pattern Mining from Videos | 2024 | VLDB | 5.1997534e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 6,880 | Real-time Distributed Co-Movement Pattern Detection on Streaming Trajectories | 2019 | VLDB |
| 2 | 8,538 | Splitter: Mining Fine-Grained Sequential Patterns in Semantic Trajectories | 2014 | VLDB |
| 3 | 1,885 | Discovery of Convoys in Trajectory Databases | 2008 | VLDB |
| 4 | 3,645 | A General and Parallel Platform for Mining Co-Movement Patterns over Large-scale Trajectories | 2017 | VLDB |
| 5 | 1,755 | Swarm: Mining Relaxed Temporal Moving Object Clusters | 2010 | VLDB |
| 6 | 12,018 | Efficient Mining of Regional Movement Patterns in Semantic Trajectories | 2017 | VLDB |
| 7 | 10,393 | Query-Aware Path Inference from Spatial Videos | 2026 | SIGMOD |
| 8 | 9,023 | CoMing: A Real-time Co-Movement Mining System for Streaming Trajectories | 2020 | SIGMOD |
| 9 | 7,453 | k/2-hop: Fast Mining of Convoy Patterns With Effective Pruning | 2019 | VLDB |
| 10 | 9,894 | Co-movement Pattern Mining from Videos | 2024 | VLDB |