2019/04/09 by Mohammad Keshavarzi, Michael Wu, Keshavarzi, Mohammad +7 · 1 citation
Computer Science · Neuroscience · #FOS: Computer and information sciences #Face Recognition and Perception #Face recognition and analysis #Human-Computer Interaction (cs.HC) #Multimedia (cs.MM) #Virtual Reality Applications and Impacts #cs.HC #cs.MM
paper · pdf · doi:10.48550/arxiv.1904.04723
arxiv created 2019/04/09 · openalex publication_date 2019/04/09 · arxiv updated 2019/04/10 · openalex created_date 2019/04/25 · openalex updated_date 2026/07/28
Virtual and augmented reality communication platforms are seen as promising modalities for next-generation remote face-to-face interactions. Our study attempts to explore non-verbal communication features in relation to their conversation context for virtual and augmented reality mediated communication settings. We perform a series of user experiments, triggering nine conversation tasks in 4 settings, each containing corresponding non-verbal communication features. Our results indicate that conversation types which involve less emotional engagement are more likely to be acceptable in virtual reality and augmented reality settings with low-fidelity avatar representation, compared to scenarios that involve high emotional engagement or intellectually difficult discussions. We further systematically analyze and rank the impact of low-fidelity representation of micro-expressions, body scale, head pose, and hand gesture in affecting the user experience in one-on-one conversations, and validate that preserving micro-expression cues plays the most effective role in improving bi-directional conversations in future virtual and augmented reality settings.