论文标题
机器人手球手势行为的定量分析
Quantitative analysis of robot gesticulation behavior
论文作者
论文摘要
社交机器人能力（例如说话手势）最好使用数据驱动的方法来避免重复并表现出可信度。但是，缺乏强大的定量方法，可以比较超出视觉评估的此类方法。在本文中，进行了定量分析，该分析比较了两种基于基于的对抗网络的手势生成方法。目的是衡量特征，例如对原始训练数据的保真度，但同时跟踪产生的手势的独创性。进行主坐标分析和procrustes统计数据，并通过将Fréchet的距离适应手势提出了新的Fréchet手势距离。这三种技术被一起采用，以弥补产生的手势的忠诚/独创性。
Social robot capabilities, such as talking gestures, are best produced using data driven approaches to avoid being repetitive and to show trustworthiness. However, there is a lack of robust quantitative methods that allow to compare such methods beyond visual evaluation. In this paper a quantitative analysis is performed that compares two Generative Adversarial Networks based gesture generation approaches. The aim is to measure characteristics such as fidelity to the original training data, but at the same time keep track of the degree of originality of the produced gestures. Principal Coordinate Analysis and procrustes statistics are performed and a new Fréchet Gesture Distance is proposed by adapting the Fréchet Inception Distance to gestures. These three techniques are taken together to asses the fidelity/originality of the generated gestures.
