Interaction analysis and joint attention tracking in augmented reality

Abstract

Multimodal research in human interaction has to consider a variety of factors, ranging from local short-time phenomena to complex interaction patterns. As of today, no single discipline engaged in communication research offers the methods and tools to investigate the full complexity continuum in a time-efficient way. A synthesis of qualitative and quantitative analysis is required to merge insights about micro-sequential structures with big data patterns. Using the example of a co-present dyadic negotiation analysis to combine methods offered by Conversation Analysis and Data Mining, we show how such a partnership can benefit each discipline and lead to insights as well as new hypotheses evaluation opportunities.

Vision-Based Technique and Issues for Multimodal Interaction in Augmented Reality

“…As presented in Neumann [29] has developed the multimodal AR interface able to remove, manipulate or add communicatively relevant multimodal information in real-time. By using an AR interception proposed by [30] and methodology explored by [29]. Pitsch et al [31] developed a tool for linguistic studies.…”