Dr. Thammathip Piumsomboon is a Research Fellow at the Empathic Computing Laboratory (ECL) exploring research in Empathic Mixed Reality for remote collaboration. Prior to his return to academia, he was a Unity Director in an Augmented Reality (AR) start-up, QuiverVision, developing mobile AR application. He received a PhD in Computer Science from the University of Canterbury in 2015, supervised by Prof. Mark Billinghurst, Prof. Andy Cockburn, and Dr. Adrian Clark. During his PhD, he was a research assistant at the Human Interface Laboratory New Zealand (HIT Lab NZ). His research focused on developing novel AR interfaces and exploring natural interaction for AR using advanced interface technology.
For more information, please visit his personal website.
Mini-Me is an adaptive avatar for enhancing Mixed Reality (MR) remote collaboration between a local Augmented Reality (AR) user and a remote Virtual Reality (VR) user. The Mini-Me avatar represents the VR user’s gaze direction and body gestures while it transforms in size and orientation to stay within the AR user’s field of view. We tested Mini-Me in two collaborative scenarios: an asymmetric remote expert in VR assisting a local worker in AR, and a symmetric collaboration in urban planning. We found that the presence of the Mini-Me significantly improved Social Presence and the overall experience of MR collaboration.
Head and eye movement can be leveraged to improve the user’s interaction repertoire for wearable displays. Head movements are deliberate and accurate, and provide the current state-of-the-art pointing technique. Eye gaze can potentially be faster and more ergonomic, but suffers from low accuracy due to calibration errors and drift of wearable eye-tracking sensors. This work investigates precise, multimodal selection techniques using head motion and eye gaze. A comparison of speed and pointing accuracy reveals the relative merits of each method, including the achievable target size for robust selection. We demonstrate and discuss example applications for augmented reality, including compact menus with deep structure, and a proof-of-concept method for on-line correction of calibration drift.
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.
Thammathip Piumsomboon, Gun A. Lee, Jonathon D. Hart, Barrett Ens, Robert W. Lindeman, Bruce H. Thomas, and Mark Billinghurst. 2018. Mini-Me: An Adaptive Avatar for Mixed Reality Remote Collaboration. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, Paper 46, 13 pages. DOI: https://doi.org/10.1145/3173574.3173620
Mikko Kytö, Barrett Ens, Thammathip Piumsomboon, Gun A. Lee, and Mark Billinghurst. 2018. Pinpointing: Precise Head- and Eye-Based Target Selection for Augmented Reality. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, Paper 81, 14 pages. DOI: https://doi.org/10.1145/3173574.3173655
Barrett Ens, Aaron Quigley, Hui-Shyong Yeo, Pourang Irani, Thammathip Piumsomboon, and Mark Billinghurst. 2018. Counterpoint: Exploring Mixed-Scale Gesture Interaction for AR Applications. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (CHI EA '18). ACM, New York, NY, USA, Paper LBW120, 6 pages. DOI: https://doi.org/10.1145/3170427.3188513
Thammathip Piumsomboon, Gun A. Lee, and Mark Billinghurst. 2018. Snow Dome: A Multi-Scale Interaction in Mixed Reality Remote Collaboration. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (CHI EA '18). ACM, New York, NY, USA, Paper D115, 4 pages. DOI: https://doi.org/10.1145/3170427.3186495
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
Thammathip Piumsomboon, Gun Lee, Robert W. Lindeman and Mark Billinghurst. 2017. Exploring Natural Eye-Gaze-Based Interaction for Immersive Virtual Reality. In 2017 IEEE Symposium on 3D User Interfaces (3DUI), pp. 36-39. https://doi.org/10.1109/3DUI.2017.7893315
Piumsomboon, T., Dey, A., Ens, B., Lee, G., & Billinghurst, M. (2019). The effects of sharing awareness cues in collaborative mixed reality. Front. Rob, 6(5).
Ens, B., Lanir, J., Tang, A., Bateman, S., Lee, G., Piumsomboon, T., & Billinghurst, M. (2019). Revisiting collaboration through mixed reality: The evolution of groupware. International Journal of Human-Computer Studies.
Piumsomboon, T., Lee, G. A., Irlitti, A., Ens, B., Thomas, B. H., & Billinghurst, M. (2019, April). On the Shoulder of the Giant: A Multi-Scale Mixed Reality Collaboration with 360 Video Sharing and Tangible Interaction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (p. 228). ACM.
Piumsomboon, T., Lee, G. A., Ens, B., Thomas, B. H., & Billinghurst, M. (2018). Superman vs giant: a study on spatial perception for a multi-scale mixed reality flying telepresence interface. IEEE transactions on visualization and computer graphics, 24(11), 2974-2982.
Hart, J. D., Piumsomboon, T., Lawrence, L., Lee, G. A., Smith, R. T., & Billinghurst, M. (2018, October). Emotion Sharing and Augmentation in Cooperative Virtual Reality Games. In Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play Companion Extended Abstracts (pp. 453-460). ACM.
Hart, J. D., Piumsomboon, T., Lee, G., & Billinghurst, M. (2018, October). Sharing and Augmenting Emotion in Collaborative Mixed Reality. In 2018 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) (pp. 212-213). IEEE.
Dey, A., Piumsomboon, T., Lee, Y., & Billinghurst, M. (2017, May). Effects of sharing physiological states of players in a collaborative virtual reality gameplay. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (pp. 4045-4056). ACM.
Piumsomboon, T., Lee, Y., Lee, G. A., Dey, A., & Billinghurst, M. (2017, June). Empathic mixed reality: Sharing what you feel and interacting with what you see. In 2017 International Symposium on Ubiquitous Virtual Reality (ISUVR) (pp. 38-41). IEEE.
Lee, G., Kim, S., Lee, Y., Dey, A., Piumsomboon, T., Norman, M., & Billinghurst, M. (2017, October). Mutually Shared Gaze in Augmented Video Conference. In Adjunct Proceedings of the 2017 IEEE International Symposium on Mixed and Augmented Reality, ISMAR-Adjunct 2017 (pp. 79-80). Institute of Electrical and Electronics Engineers Inc..
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.
Ens, B., Quigley, A. J., Yeo, H. S., Irani, P., Piumsomboon, T., & Billinghurst, M. (2017). Exploring mixed-scale gesture interaction. SA'17 SIGGRAPH Asia 2017 Posters.
Ens, B., Quigley, A., Yeo, H. S., Irani, P., & Billinghurst, M. (2017, November). Multi-scale gestural interaction for augmented reality. In SIGGRAPH Asia 2017 Mobile Graphics & Interactive Applications (p. 11). ACM.
We present a multi-scale gestural interface for augmented reality applications. With virtual objects, gestural interactions such as pointing and grasping can be convenient and intuitive, however they are imprecise, socially awkward, and susceptible to fatigue. Our prototype application uses multiple sensors to detect gestures from both arm and hand motions (macro-scale), and finger gestures (micro-scale). Micro-gestures can provide precise input through a belt-worn sensor configuration, with the hand in a relaxed posture. We present an application that combines direct manipulation with microgestures for precise interaction, beyond the capabilities of direct manipulation alone.
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.