Engagement detection based on mutli-party cues for human robot interaction
Engagement detection based on mutli-party cues for human robot interaction
复制标题
基于多方线索的人机交互参与检测
DOI：
10.1109/acii.2015.7344593
复制
发表时间：
2015
期刊：
影响因子：
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通讯作者：
M. Chetouani
中科院分区：
文献类型：
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作者：
Hanan Salam;M. Chetouani
在本文中，我们解决的问题，自动检测参与多方人机交互场景。我们的目的是调查在多大程度上，我们能够推断出一个组的实体之一的参与，仅仅基于其他实体的线索存在于互动。在具有3个实体的场景中：2个参与者和一个机器人，我们提取与每个实体相关的行为线索，然后仅基于这些实体的线索以及它们的组合来构建模型，以预测每个参与者的参与程度。个人水平的交叉验证表明，我们能够检测参与者的参与问题，仅使用机器人的行为线索，与使用参与者自己的线索相比，具有很高的准确性（75.91%对74.32%）。此外，使用其他参与者的行为线索也是信息性的，其中它允许以平均62.15%的准确度检测所讨论的参与者的参与。另一参与者的特征与所讨论的参与者的参与标签之间的相关性表明两个参与者之间的高凝聚力。此外，两个参与者之间最显著相关特征的相似性表明双方之间的高度同步。
In this paper, we address the problematic of automatic detection of engagement in multi-party Human-Robot Interaction scenarios. The aim is to investigate to what extent are we able to infer the engagement of one of the entities of a group based solely on the cues of the other entities present in the interaction. In a scenario featuring 3 entities: 2 participants and a robot, we extract behavioural cues that concern each of the entities, we then build models based solely on each of these entities' cues and on combinations of them to predict the engagement level of each of the participants. Person-level cross validation shows that we are capable of detecting the engagement of the participant in question using solely the behavioural cues of the robot with a high accuracy compared to using the participant's cues himself (75.91% vs. 74.32%). Moreover using the behavioural cues of the other participant is also informative where it permits the detection of the engagement of the participant in question at an accuracy of 62.15% on average. The correlation between the features of the other participant with the engagement labels of the participant in question suggests a high cohesion between the two participants. In addition, the similarity of the most significantly correlated features among the two participants suggests a high synchrony between the two parties.