FSOCO: フォーミュラスタジアム向けコーン検出データセット
FSOCO: The Formula Student Objects in Context Dataset
学生フォーミュラ無人走行向けに、コーン検出用のバウンディングボックスとセグメンテーションマスクを人手で注釈付けした共同データセットを構築し、その品質管理手法と有効性を示した論文。
著者: Niclas Vödisch, David Dodel, Michael Schötz
分類: cs.CV, cs.LG, cs.RO
原文アブストラクト
This paper presents the FSOCO dataset, a collaborative dataset for vision-based cone detection systems in Formula Student Driverless competitions. It contains human annotated ground truth labels for both bounding boxes and instance-wise segmentation masks. The data buy-in philosophy of FSOCO asks student teams to contribute to the database first before being granted access ensuring continuous growth. By providing clear labeling guidelines and tools for a sophisticated raw image selection, new annotations are guaranteed to meet the desired quality. The effectiveness of the approach is shown by comparing prediction results of a network trained on FSOCO and its unregulated predecessor. The FSOCO dataset can be found at https://fsoco.github.io/fsoco-dataset/.
