“Deep Learning for Action Recognition in Augmented Reality Assistance Systems” by Schröder and Ritter
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Entry Number: 75
Title:
- Deep Learning for Action Recognition in Augmented Reality Assistance Systems
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Abstract:
Recent advances in the development of optical head-mounted displays (HMDs), such as the Microsoft HoloLens, Google Glass, or Epson Moverio, which overlay visual information directly in the user’s field of vision, have opened up new possibilities for augmented reality (AR) applications. We propose a system that uses such an optical HMD to assist the user during goal-oriented activities (e.g. manufacturing work) in an intuitive and unobtrusive way (Essig et al. 2016). To this end, our system observes and recognizes the user’s actions and generates context-sensitive feedback. Figure 1 shows an overview of our approach, exemplified with the task of assembling a bird house.
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