论文标题
ic！您是否认识我在做什么？：多模式的人类行动识别多感官的ICUB机器人
iCub! Do you recognize what I am doing?: multimodal human action recognition on multisensory-enabled iCub robot
论文作者
论文摘要
这项研究使用多感官数据（即颜色和深度）在多模式人类机器人相互作用的背景下识别人类行为。在这里，我们采用了ICUB机器人，通过在20个对象上使用四种不同的工具来观察人类合作伙伴的预定义动作。我们表明，与单个模式训练的模型相比，提出的三个彩色相机和一个深度传感器的互补特征和一个深度传感器的互补特性相比，我们表明了拟议的多模式集合学习的互补特性。结果表明，提出的模型可以部署在ICUB机器人上，该机器人需要多模式的行动识别，包括社交任务，例如特定于合作伙伴的适应和上下文行为理解，以提及一些。
This study uses multisensory data (i.e., color and depth) to recognize human actions in the context of multimodal human-robot interaction. Here we employed the iCub robot to observe the predefined actions of the human partners by using four different tools on 20 objects. We show that the proposed multimodal ensemble learning leverages complementary characteristics of three color cameras and one depth sensor that improves, in most cases, recognition accuracy compared to the models trained with a single modality. The results indicate that the proposed models can be deployed on the iCub robot that requires multimodal action recognition, including social tasks such as partner-specific adaptation, and contextual behavior understanding, to mention a few.
