The Effect of Embodied Interaction in Visual-Spatial Navigation

被引:12
|
作者
Zhang, Ting [1 ]
Li, Yu-Ting [1 ]
Wachs, Juan P. [1 ]
机构
[1] Purdue Univ, 315 N Grant St, W Lafayette, IN 47907 USA
关键词
Embodied interaction; attention inference; Bayesian network; gesture interaction; multimodal interaction; BAYESIAN NETWORKS; UTILITY FUNCTION; ATTENTION; INTERRUPTION; INFORMATION; ALGORITHMS; GESTURES;
D O I
10.1145/2953887
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article aims to assess the effect of embodied interaction on attention during the process of solving spatio-visual navigation problems. It presents a method that links operator's physical interaction, feedback, and attention. Attention is inferred through networks called Bayesian Attentional Networks (BANs). BANs are structures that describe cause-effect relationship between attention and physical action. Then, a utility function is used to determine the best combination of interaction modalities and feedback. Experiments involving five physical interaction modalities (vision-based gesture interaction, glove-based gesture interaction, speech, feet, and body stance) and two feedback modalities (visual and sound) are described. The main findings are: (i) physical expressions have an effect in the quality of the solutions to spatial navigation problems; (ii) the combination of feet gestures with visual feedback provides the best task performance.
引用
收藏
页数:36
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