Synth-Yard-MCMOT-1 – A synthetic multi camera multi object dataset in the context of yard logistics

<p>The dataset "Synth-Yard-MCMOT-1" is a novel image dataset for multi-camera multi-object tracking (MCMOT). It&nbsp;is the first of its kind to be generated in a virtual environment with the main focus on the tracking of trucks in yard logistics environments. The dataset consists of a total of 12,008 images generated by eight different cameras. The images contain 44,232 bounding boxes and segmentation masks and 52&nbsp;individual tracks. Additionally, we provide a ninth camera, which is used to generate unified ground-truth information for the whole scene from an orthographic, top-down perspective comparable to a bird&rsquo;s eye or map-view. The purpose of this dataset is to provide yard management systems with relevant data, which can be employed when aiming to determine the exact position of a truck and specifically identifying which gateway or designated parking spot it is located in.&nbsp;<br>Additionally in this dataset we added the annotations in the COCO-style format as well as the raw image-data.<br>Initial benchmarks for single-camera tracking demonstrate a mean IDF1 score of 0.96 and a mean MOTA score of 0.94, laying the baseline for computing world coordinates via MCMOT.<br><br><span>This work is part of the project &ldquo;Silicon Economy Logistics </span><span>Ecosystem&rdquo; which is funded by the German Federal Ministry </span><span>of Transport and Digital Infrastructure. <br></span><span>This research has partly been funded by the Federal Ministry </span><span>of Education and Research of Germany and the state of North-</span><span>Rhine Westphalia as part of the Lamarr-Institute&nbsp; for Machine </span><span>Learning and Artificial Intelligence. <br></span><span>We would like to thank our colleagues Julian Hinxlage, </span><span>Oleg Belov, Habib Kilic, Nicole Wagner-Hanl, Leona Cerimi, </span><span>Antonia Ponikarov and Nico Lindemann for their support.</span></p> <p><span>The code to create this dataset can be found here: </span><span>https://git.openlogisticsfoundation.org/silicon-economy/base/ml-toolbox/</span><span>synth-data-mcmot</span></p> <div> <div>&nbsp;</div> <div>&nbsp;</div> </div> <p>&nbsp;</p>