Augmented reality (AR) is emerging in visual search tasks for increasingly immersive interactions with virtual objects. We propose an AR approach providing visual and audio hints along with gazeassisted instant post-task feedback for search tasks based on mobile head-mounted display (HMD). The target case was a book-searching task, in which we aimed to explore the effect of the hints together with the task feedback with two hypotheses. H1: Since visual and audio hints can positively affect AR search tasks, the combination outperforms the individuals. H2: The gaze-assisted instant post-task feedback can positively affect AR search tasks. The proof-of-concept was demonstrated by an AR app in HMD and a comprehensive user study (n=96) consisting of two sub-studies, Study I (n=48) without task feedback and Study II (n=48) with task feedback. Following quantitative and qualitative analysis, our results partially verified H1 and completely verified H2, enabling us to conclude that the synthesis of visual and audio hints conditionally improves the AR visual search task efficiency when coupled with task feedback.

Industrial process tomography (IPT) is a specialized imaging technique widely used in industrial scenarios for process supervision and control. Today, augmented/mixed reality (AR/MR) is increasingly being adopted in many industrial occasions, even though there is still an obvious gap when it comes to IPT. To bridge this gap, we propose the first systematic AR approach using optical see-through (OST) head mounted displays (HMDs) with comparative evaluation for domain users towards IPT visualization analysis. The proof-of-concept was demonstrated by a within-subject user study (n=20) with counterbalancing design. Both qualitative and quantitative measurements were investigated. The results showed that our AR approach outperformed conventional settings for IPT data visualization analysis in bringing higher understandability, reduced task completion time, lower error rates for domain tasks, increased usability with enhanced user experience, and a better recommendation level. We summarize the findings and suggest future research directions for benefiting IPT users with AR/MR.