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Experiment results for the paper "Uncertainty-Aware Ship Location Estimation using Multiple Cameras in Coastal Areas" to appear in MDM'2024

<p>After decompression, there are 16 folders which corresponding to the 16 multi-camera settings in the paper.</p> <p>&nbsp;</p> <p>Under each folder, there are two files: trajs.csv and trajsGuess.csv.</p> <p>&nbsp;</p> <p>1. trajs.csv contains the trajectories of ships that are located inside the monitored area of the mult-camera setting.</p> <p>&nbsp; &nbsp; The first four columns are MMSI (ship identity), timestamp, lon, and lat.</p> <p>&nbsp; &nbsp; The following columns are the corresponding pixel of the coordinate (lon, lat) in each camera, where (-1,-1) means (lon, lat) is outside the monitored area by a camera.</p> <p>&nbsp; &nbsp; A pixel is a pair of integers.&nbsp;</p> <p>&nbsp; &nbsp; xPos1 and yPos1 are for the 1st camera, and xPos2 and yPos2 are for the 2nd camera, and so on so forth.</p> <p>&nbsp;</p> <p>2. trajsGuess.csv contains the estimated ship locations by using the proposed approach in the paper.</p> <p>&nbsp; &nbsp; There are 6 columns.</p> <p>&nbsp; &nbsp; The 1st column is timestamp.</p> <p>&nbsp; &nbsp; The 2nd column is used to distinguish between the different pixel polygon intersections.</p> <p>&nbsp; &nbsp; The 3rd column and the 4th column can be either a pixel coordinate or a spatial point coordinate in lon/lat.</p> <p>&nbsp; &nbsp; The 5th column is either the cameraID of a pixel, or the order of a boundary point for a spatial polygon. The cameraID starts from 1.</p> <p>&nbsp; &nbsp; The 6th column is the type of the record, which can be</p> <p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; pixel,</p> <p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; or intersection1 (a polygon),</p> <p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; or center1 (center of intersection1),</p> <p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; or intersection2 (a polygon),</p> <p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; or center2 (center of intersection2).</p> <p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Note that intersection2 and center2 appear rarely in the 6th column.</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0