Mixed Reality for Collaboration

Augmenting interaction with digital information

Mixed reality (AR/VR) will soon change how we interact other people and information, allowing us to interact across time and space. This project explores fundamental questions of how we can achieve those goals, and how mixed reality interfaces should be designed to enable these new forms of interaction.

Smaller subprojects have addressed the following questions:

We are interested in exploring the use of mixed reality to enable new forms of communication across distance (where people are remote from one another) and across time (pre-recorded for use in the future).


  1. Martin Feick, Terrance Mok, Anthony Tang, Lora Oehlberg, and Ehud Sharlin. (2018). Perspective on and Re-Orientation of Physical Proxies in Object-Focused Remote Collaboration. In CHI 2018: Proceedings of the 2018 SIGCHI Conference on Human Factors in Computing Systems, Paper 281. (conference).
    Acceptance: 25.7% - 667/2595. Notes: Honourable Mention Award - Top 5% of all submissions; 10 pages.
  2. Tran Pham, Jo Vermeulen, Anthony Tang, and Lindsay MacDonald. (2018). Scale Impacts Elicited Gestures for Manipulating Holograms: Implications for AR Gesture Design. In DIS 2018: Proceedings of the 2018 Conference on Designing Interactive Systems, 227–240. (conference).
    Acceptance: 23% - 92/405. Notes: Includes supplemental material illustrating the referents used in the study..
  3. Anthony Tang, Omid Fakourfar, Carman Neustaedter, and Scott Bateman. (2017). Collaboration in 360° Videochat: Challenges and Opportunities. In DIS 2017: Conference on Designing Interactive Systems 2017 , 1327–1339. (conference).
    Acceptance: 24% - 110/458. Notes: Appendix material: http://dspace.ucalgary.ca/handle/1880/51950.
  4. Omid Fakourfar, Kevin Ta, Richard Tang, Scott Bateman, and Anthony Tang. (2016). Stabilized Annotations for Mobile Remote Assistance. In CHI 2016: Proceedings of the 2016 SIGCHI Conference on Human Factors in Computing Systems, 1548–1560. (conference).
    Acceptance: 565/2435 - 23.2%.