Dr. Barrett Ens is a Postdoctoral Research Fellow with experience designing interfaces for head-worn displays, aimed at pushing wearable capabilities beyond current micro-interactions. By incorporating new interactive devices and techniques with Augmented Reality, his previous work explored interfaces that support multi-view, analytic tasks for in-situ mobile workers and other everyday users. Along with additional experience in collaborative and social computing, 3D immersive interfaces, and visual analytics, Barrett brings his skills to the Empathic Computing Lab with hopes of creating rich collaborative experiences that support intuitive interaction with high-level cognitive tasks.
Barrett completed his PhD in Computer Science at the University of Manitoba under the supervision of Pourang Irani. Previously, he received a BSc in Computer Science with first class honours from the University of Manitoba and a BMus from the University of Calgary, where he studied classical guitar and specialized in Music Theory. In 2015 and 2016, Barrett completed a pair of research internships at Autodesk Research in Toronto under the supervision of Tovi Grossman and Fraser Anderson. In 2012, he joined Michael Haller at the Media Interaction Lab in Hagenberg, Austria in a summer exchange program. He has contributed to the program committees for the Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) and the ACM Symposium on Spatial User Interaction (SUI).
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.
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
Lynda Gerry, Barrett Ens, Adam Drogemuller, Bruce Thomas, and Mark Billinghurst. 2018. Levity: A Virtual Reality System that Responds to Cognitive Load. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems (CHI EA '18). ACM, New York, NY, USA, Paper LBW610, 6 pages. DOI: https://doi.org/10.1145/3170427.3188479