Symphony Lake Dataset 2017

Symphony Lake Dataset

Symphony Lake Dataset consists of 121 visual surveys of a lakeshore over more than three years in Metz, France. Unique from roadway datasets, it adds breadth to a space at a time when larger and more diverse datasets are needed to train data hungry machine learning methods. Over 5 million images from an unmanned surface vehicle capture the unstructured, natural environment as it evolved over time. Significant variation in appearance is present on time scales of weeks, seasons, and years. Success in this space may demonstrate advancements in perception, SLAM, and environment monitoring.

On top of the raw surveys, some pre-processed results are also available:

  • Symphony Lake Dataset Visual Benchmark
  • Symphony Lake Dataset image pair dataset
  • Symphony Lake Dataset 2D localisation and mapping

Full Dataset - Raw Surveys - Download per Survey

Year 2014 Year 2015 Year 2016 Year 2017

Survey Date (YY-MM-DD) Downsampled Dataset (5%) Full Dataset Laser Data Youtube Preview
170217 170217 (245M) 170217 (4.8G) 170217 (63M)
170223 170223 (208M) 170223 (4.1G) 170223 (52M)
170303 170303 (195M) 170303 (3.9G) 170303 (55M)
170307 170307 (201M) 170307 (4.0G) 170307 (52M)
170313 170313 (191M) 170313 (3.8G) 170313 (56M)
170320 170320 (195M) 170320 (3.9G) 170320 (50M)
170327 170327 (207M) 170327 (4.1G) 170327 (55M)
170403 170403 (179M) 170403 (3.5G) 170403 (47M)

References

Please cite the following paper if you use the dataset:

  • Griffith, Shane; Chahine, Georges; Pradalier, Cédric; Symphony Lake Dataset, IJRR, 2017.

Relevant Papers:

  • Griffith, Shane; Pradalier, Cédric; Reprojection Flow for Image Registration Across Seasons, British Machine Vision Conference (BMVC), 2016
  • Griffith, Shane; Pradalier, Cédric; Survey Registration for Long-Term Natural Environment Monitoring, Journal of Field Robotics, 2016