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+@article{miller2017,
+author = {Martin Miller and Soon-Jo Chung and Seth Hutchinson},
+title ={The Visual–Inertial Canoe Dataset},
+journal = {The International Journal of Robotics Research},
+volume = {37},
+number = {1},
+pages = {13-20},
+year = {2018},
+doi = {10.1177/0278364917751842},
+
+URL = { 
+        https://doi.org/10.1177/0278364917751842
+    
+},
+eprint = { 
+        https://doi.org/10.1177/0278364917751842
+    
+}
+,
+    abstract = { We present a dataset collected from a canoe along the Sangamon River in Illinois. The canoe was equipped with a stereo camera, an inertial measurement unit (IMU), and a global positioning system (GPS) device, which provide visual data suitable for stereo or monocular applications, inertial measurements, and position data for ground truth. We recorded a canoe trip up and down the river for 44 minutes covering a 2.7 km round trip. The dataset adds to those previously recorded in unstructured environments and is unique in that it is recorded on a river, which provides its own set of challenges and constraints that are described in this paper. The dataset is stored on the Illinois Data Bank and can be accessed at: https://doi.org/10.13012/B2IDB-9342111\_V1. }
+}
+
+