Evaluation of human-computer interface for optical see-through augmented reality system
Qianying Wang, Dayuan Yan, Dongdong Weng, Zeyong Qi · 2011
Presenting effective augmenting information is helpful for users to perceive and interact in augmented reality systems. In this paper, a novel method for evaluating the human-computer interface in optical see-through augmented reality system is proposed. The main contribution presented in this paper is a user-based study that adopts the Radius Basis Function (RBF) neural network to model the relationship between the human-computer interface and user experience. Several important guidelines to design a successful human-computer interface in optical see-through AR are concluded by experiment. In addition, questionnaire results demonstrate the validity of the evaluation model.