论文标题
Blassetet-临床现实世界中的床内动作识别和定性半同步MOCAP数据集
BlanketSet -- A clinical real-world in-bed action recognition and qualitative semi-synchronised MoCap dataset
论文作者
论文摘要
基于临床内部视频的人类运动分析是几种相关生物医学应用的非常相关的计算机视觉主题。然而，用于深度学习方法的主要公共大型数据集（例如ImageNet或3DPW）缺乏这些临床情况的带注释的示例。为了解决此问题，我们介绍了Blassetet，这是在医院病床中执行的RGB-IR-D动作识别数据集。该数据集有可能帮助弥合更一般的大型数据集中获得的改进，以解决这些临床方案。有关如何访问数据集的信息，请访问https://rdm.inesctec.pt/dataset/nis-2022-004。
Clinical in-bed video-based human motion analysis is a very relevant computer vision topic for several relevant biomedical applications. Nevertheless, the main public large datasets (e.g. ImageNet or 3DPW) used for deep learning approaches lack annotated examples for these clinical scenarios. To address this issue, we introduce BlanketSet, an RGB-IR-D action recognition dataset of sequences performed in a hospital bed. This dataset has the potential to help bridge the improvements attained in more general large datasets to these clinical scenarios. Information on how to access the dataset is available at https://rdm.inesctec.pt/dataset/nis-2022-004.
