论文标题
从文本指令中产生虚拟运动的质量评估案例研究
Towards Generating Virtual Movement from Textual Instructions A Case Study in Quality Assessment
论文作者
论文摘要
许多应用领域，从严重的健康游戏到机器人的演示学习，可以从从文本说明中提取的大型身体运动数据集中受益。自动生成相应动作（例如练习）和对这些运动的验证的说明的解释是艰巨的任务。在本文中，我们描述了实现自动提取的第一步。我们使用Kinect的七个业余表演者的帮助，以随机顺序记录了五个不同的练习。在录制过程中，我们发现每个人类表演者都得到了相同的文本说明，也对相同的练习进行了不同的解释。我们使用众包方法对数据进行了质量评估研究，并测试了不同类型的可视化的评价者一致性，基于RGBB的可视化显示了注释者之间的最佳一致性。
Many application areas ranging from serious games for health to learning by demonstration in robotics, could benefit from large body movement datasets extracted from textual instructions accompanied by images. The interpretation of instructions for the automatic generation of the corresponding motions (e.g. exercises) and the validation of these movements are difficult tasks. In this article we describe a first step towards achieving automated extraction. We have recorded five different exercises in random order with the help of seven amateur performers using a Kinect. During the recording, we found that the same exercise was interpreted differently by each human performer even though they were given identical textual instructions. We performed a quality assessment study based on that data using a crowdsourcing approach and tested the inter-rater agreement for different types of visualizations, where the RGBbased visualization showed the best agreement among the annotators.
