We have been developing a remote collaboration system with Empathy Glasses, a head worn display designed to create a stronger feeling of empathy between remote collaborators. To do this, we combined a head- mounted see-through display with a facial expression recognition system, a heart rate sensor, and an eye tracker. The goal is to enable a remote person to see and hear from another person's perspective and to understand how they are feeling. In this way, the system shares non-verbal cues that could help increase empathy between remote collaborators.
Y. Lee, K. Masai, K. Kunze, M. Sugimoto and M. Billinghurst. 2016. A Remote Collaboration System with Empathy Glasses. 2016 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct)(ISMARW), Merida, pp. 342-343. http://doi.ieeecomputersociety.org/10.1109/ISMAR-Adjunct.2016.0112
Gun Lee, Seungwon Kim, Youngho Lee, Arindam Dey, Thammathip Piumsomboon, Mitchell Norman and Mark Billinghurst. 2017. Improving Collaboration in Augmented Video Conference using Mutually Shared Gaze. In Proceedings of ICAT-EGVE 2017 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments, pp. 197-204. http://dx.doi.org/10.2312/egve.20171359
Lee, Y., Piumsomboon, T., Ens, B., Lee, G., Dey, A., & Billinghurst, M. (2017, November). A gaze-depth estimation technique with an implicit and continuous data acquisition for OST-HMDs. In Proceedings of the 27th International Conference on Artificial Reality and Telexistence and 22nd Eurographics Symposium on Virtual Environments: Posters and Demos (pp. 1-2). Eurographics Association.
The rapid developement of machine learning algorithms can be leveraged for potential software solutions in many domains including techniques for depth estimation of human eye gaze. In this paper, we propose an implicit and continuous data acquisition method for 3D gaze depth estimation for an optical see-Through head mounted display (OST-HMD) equipped with an eye tracker. Our method constantly monitoring and generating user gaze data for training our machine learning algorithm. The gaze data acquired through the eye-tracker include the inter-pupillary distance (IPD) and the gaze distance to the real andvirtual target for each eye.
Piumsomboon, T., Day, A., Ens, B., Lee, Y., Lee, G., & Billinghurst, M. (2017, November). Exploring enhancements for remote mixed reality collaboration. In SIGGRAPH Asia 2017 Mobile Graphics & Interactive Applications (p. 16). ACM.