Scalable Complex Event Processing on Video Streams
Summary: Bobsled enables efficient complex event queries over video streams, leveraging temporal patterns beyond simple selection/aggregation. Throughput gains of 2.4–11.6x over state-of-the-art with no accuracy loss demonstrate scalable, real-time video CEP. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Chenxia Han (Chinese University of Hong Kong)
- 2. Chaokun Chang (Chinese University of Hong Kong)
- 3. Srijan Srivastava (Centre For Perceptual and Interactive Intelligence)
- 4. Yao Lu (National University of Singapore)
- 5. Eric Lo (Chinese University of Hong Kong)
BibTeX Citation
@inproceedings{han_sigmod25,
title = {{Scalable Complex Event Processing on Video Streams}},
author = {Han, Chenxia and Chang, Chaokun and Srivastava, Srijan and Lu, Yao and Lo, Eric},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725419},
url = {https://dl.acm.org/doi/10.1145/3725419},
year = {2025}
}
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