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Visual Road

A Video Data Management Benchmark

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About Visual Road

Video database management systems (VDBMSs) have recently re-emerged as an active area of research and development. To accelerate innovation in this area, we present Visual Road, a benchmark that evaluates the performance of these systems. Visual Road comes with a dataset generator and a suite of benchmark queries over cameras positioned within a simulated metropolitan environment. Visual Road's video data is automatically generated with a high degree of realism, and annotated using a modern simulation and visualization engine. This allows for VDBMS performance evaluation while scaling up the size of the input data.

Visual Road is designed to evaluate a broad variety of VDBMSs: real-time systems, systems for longitudinal analytical queries, systems processing traditional videos, and systems designed for 360◦ videos. Visual Road relies on the Unreal Engine for physical simulation and rendering, and the Carla simulator as a back-end engine (including its assets, geographic elements, and actor automation logic).

Visual Road architecture diagram

People

Sample Traffic Camera Videos

The following videos are representative of the traffic cameras found in a synthetic Visual Road dataset:

Rain with light traffic
Postpluvial with heavy traffic
Postpluvial with heavy auto and foot traffic
Sunny with moderate foot traffic

Pregenerated Datasets

Name Scale Resolution Duration Version Configuration Download
1K-Short-1 1 1K (960x540) 15 min 1 Link 1k-short.tar.gz
1K-Short-2 2 1K (960x540) 15 min 1 Link 1k-short-2.tar.gz
1K-Long-4 4 1K (960x540) 60 min 1 0x75BCD15 Coming soon!
2K-Short-2 2 2K (1920x1080) 15 min 1 Link 2k-short-2.tar.gz
2K-Long-4 4 2K (1920x1080) 60 min 1 0x75BCD15 Coming soon!
4K-Short-1 1 4K (3840x2160) 15 min 1 Link 4k-short.tar.gz
4K-Long-2 2 4K (3840x2160) 60 min 1 0x75BCD15 Coming soon!
4K-Long-4 4 4K (3840x2160) 60 min 1 0x75BCD15 Coming soon!

Share your dataset configuration!

If you’ve generated a dataset and would like to share its configuration with the world, please post it here with the details! To view a list of dataset configurations, please click here.

Related Publications

Acknowledgments

This work is supported by the NSF through grants CCF-1703051, IIS-1546083, CCF-1518703, and CNS-1563788; DARPA award FA8750-16-2-0032; DOE award DE-SC0016260; a Google Faculty Research Award; an award from the University of Washington Reality Lab; gifts from the Intel Science and Technology Center for Big Data, Intel Corporation, Adobe, Amazon, Facebook, Huawei, and Google; and by CRISP, one of six centers in JUMP, a Semiconductor Research Corporation (SRC) program sponsored by DARPA.