Co-movement Pattern Mining from Videos
Summary: First study of co-movement mining from surveillance video: defines camera-based spatio-temporal proximity and proves hardness. Presents TCS-tree index, sequence-ahead pruning, sliding-window enumeration and hashing-based dominance elimination; evaluated on a 1169-camera DB, much faster than Apriori/CMC and produces GPS-comparable patterns. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Dongxiang Zhang (Zhejiang University)
- 2. Teng Ma (Zhejiang University)
- 3. Junnan Hu (Zhejiang University)
- 4. Yijun Bei (Zhejiang University)
- 5. Kian-Lee Tan (National University of Singapore)
- 6. Gang Chen (Zhejiang University)
BibTeX Citation
@article{zhang_vldb24,
title = {{Co-movement Pattern Mining from Videos}},
author = {Zhang, Dongxiang and Ma, Teng and Hu, Junnan and Bei, Yijun and Tan, Kian-Lee and Chen, Gang},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {3},
pages = {604--616},
doi = {10.14778/3632093.3632119},
url = {https://doi.org/10.14778/3632093.3632119},
year = {2024}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,589 | Query-Aware Path Inference from Spatial Videos | 2026 | SIGMOD | 4.9793485e-05 |
| 11,111 | MAST: Towards Efficient Analytical Query Processing on Point Cloud Data | 2025 | SIGMOD | 4.9793485e-05 |
| 11,247 | Mining Platoon Patterns from Traffic Videos | 2025 | VLDB | 4.9793485e-05 |
| 11,509 | Predictive and Near-Optimal Sampling for View Materialization in Video Databases | 2024 | SIGMOD | 4.9793485e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,783 | Swarm: Mining Relaxed Temporal Moving Object Clusters | 2010 | VLDB | 9.6511944e-05 |
| 1,942 | Discovery of Convoys in Trajectory Databases | 2008 | VLDB | 9.3285345e-05 |
| 3,010 | A Unified Approach to Route Planning for Shared Mobility | 2018 | VLDB | 7.7554999e-05 |
| 3,411 | Spatial and Temporal Constrained Ranked Retrieval over Videos | 2022 | VLDB | 7.3253532e-05 |
| 3,696 | A General and Parallel Platform for Mining Co-Movement Patterns over Large-scale Trajectories | 2017 | VLDB | 7.0918941e-05 |
| 3,950 | Visual Road: A Video Data Management Benchmark | 2019 | SIGMOD | 6.9050253e-05 |
| 4,495 | Evaluating Temporal Queries Over Video Feeds | 2021 | SIGMOD | 6.5769374e-05 |
| 7,026 | Real-time Distributed Co-Movement Pattern Detection on Streaming Trajectories | 2019 | VLDB | 5.6180637e-05 |
| 7,600 | k/2-hop: Fast Mining of Convoy Patterns With Effective Pruning | 2019 | VLDB | 5.4870282e-05 |
| 9,193 | CoMing: A Real-time Co-Movement Mining System for Streaming Trajectories | 2020 | SIGMOD | 5.2103978e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 8,799 | MoveMine: Mining Moving Object Databases | 2010 | SIGMOD |
| 2 | 8,706 | Splitter: Mining Fine-Grained Sequential Patterns in Semantic Trajectories | 2014 | VLDB |
| 3 | 12,481 | MoveMine 2.0: Mining Object Relationships from Movement Data | 2014 | VLDB |
| 4 | 10,589 | Query-Aware Path Inference from Spatial Videos | 2026 | SIGMOD |
| 5 | 9,193 | CoMing: A Real-time Co-Movement Mining System for Streaming Trajectories | 2020 | SIGMOD |
| 6 | 7,026 | Real-time Distributed Co-Movement Pattern Detection on Streaming Trajectories | 2019 | VLDB |
| 7 | 7,600 | k/2-hop: Fast Mining of Convoy Patterns With Effective Pruning | 2019 | VLDB |
| 8 | 12,313 | Efficient Mining of Regional Movement Patterns in Semantic Trajectories | 2017 | VLDB |
| 9 | 3,696 | A General and Parallel Platform for Mining Co-Movement Patterns over Large-scale Trajectories | 2017 | VLDB |
| 10 | 11,247 | Mining Platoon Patterns from Traffic Videos | 2025 | VLDB |