Summary

Recent advances in augmented, mixed, and virtual reality, coupled with the need to perform analysis and decision-making on large-scale collections of volumetric images stimulate the research in immersive analytics. Volumetric data is ubiquitous, and fields that need to interpret and analyze them to support their activities are numerous. Neuroscience, geology, and material science are some examples, but there are entire industries that rely heavily on 3D data, for example, healthcare, construction, quality control, and security. While tools like CAVEs have been able to provide compelling immersive environments (Morehead et al., 2014), current low-cost AR/VR headsets have paved the way for a new era where data analysis and research hypothesis formulation can take advantage of the immersive dimension, by leveraging a unique tool like syGlass (Pidhorskyi et al., 2018). This requires the development of novel methods that integrate the power of computer vision and machine learning with the immersive user experience to fully unleash its potential.

References

  1. arXiv
    syGlass: Interactive Exploration of Multidimensional Images Using Virtual Reality Head-mounted Displays Pidhorskyi, S., Morehead, M., Jones, Q., Spirou, G., and Doretto, G. arXiv.org:1804.08197, 2018. abstract bibTeX arXiv pdf
  2. 3DUI
    BrainTrek: An Immersive Environment for Investigating Neuronal Tissue Morehead, M., Jones, Q., Blatt, J., Holcomb, P., Schultz, J., DeFanti, T., Ellisman, M., Doretto, G., and Spirou, G. A. In Proceedings of the IEEE Symposium on 3D User Interfaces, 2014. abstract bibTeX pdf