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Mixed Reality enables hybrid workspaces where physical and virtual monitors are adaptively created and moved to suit the current environment and needs. However, in shared settings, individual users' workspaces are rarely aligned and can vary significantly in the number of monitors, available physical space, and workspace layout, creating inconsistencies between workspaces which may cause confusion and reduce collaboration. We present Desk2Desk, an optimization-based approach for remote collaboration in which the hybrid workspaces of two collaborators are fully integrated to enable immersive side-by-side collaboration. The optimization adjusts each user's workspace in layout and number of shared monitors and creates a mapping between workspaces to handle inconsistencies between workspaces due to physical constraints (e.g. physical monitors). We show in a user study how our system adaptively merges dissimilar physical workspaces to enable immersive side-by-side collaboration, and demonstrate how an optimization-based approach can effectively address dissimilar physical layouts., Comment: ACM Symposium on User Interface Software and Technology (UIST '24)

Generative AI tools can provide people with the ability to create virtual environments and scenes with natural language prompts. Yet, how people will formulate such prompts is unclear -- particularly when they inhabit the environment that they are designing. For instance, it is likely that a person might say, "Put a chair here", while pointing at a location. If such linguistic features are common to people's prompts, we need to tune models to accommodate them. In this work, we present a wizard-of-oz elicitation study with 22 participants, where we studied people's implicit expectations when verbally prompting such programming agents to create interactive VR scenes. Our findings show that people prompt with several implicit expectations: (1) that agents have an embodied knowledge of the environment; (2) that agents understand embodied prompts by users; (3) that the agents can recall previous states of the scene and the conversation, and that (4) agents have a commonsense understanding of objects in the scene. Further, we found that participants prompt differently when they are prompting in situ (i.e. within the VR environment) versus ex situ (i.e. viewing the VR environment from the outside). To explore how our could be applied, we designed and built Oastaad, a conversational programming agent that allows non-programmers to design interactive VR experiences that they inhabit. Based on these explorations, we outline new opportunities and challenges for conversational programming agents that create VR environments., Comment: Accepted at ACM 2024 Designing Interactive Systems (DIS)

Live and pre-recorded video tutorials are an effective means for teaching physical skills such as cooking or prototyping electronics. A dedicated cameraperson following an instructor's activities can improve production quality. However, instructors who do not have access to a cameraperson's help often have to work within the constraints of static cameras. We present Stargazer, a novel approach for assisting with tutorial content creation with a camera robot that autonomously tracks regions of interest based on instructor actions to capture dynamic shots. Instructors can adjust the camera behaviors of Stargazer with subtle cues, including gestures and speech, allowing them to fluidly integrate camera control commands into instructional activities. Our user study with six instructors, each teaching a distinct skill, showed that participants could create dynamic tutorial videos with a diverse range of subjects, camera framing, and camera angle combinations using Stargazer., Comment: To appear in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23), April 23--28, 2023, Hamburg, Germany

In this paper, we present HoloBoard, an interactive large-format pseudo-holographic display system for lecture-based classes. With its unique properties of immersive visual display and transparent screen, we designed and implemented a rich set of novel interaction techniques like immersive presentation, role-play, and lecturing behind the scene that is potentially valuable for lecturing in class. We conducted a controlled experimental study to compare a HoloBoard class with a normal class by measuring students' learning outcomes and three dimensions of engagement (i.e., behavioral, emotional, and cognitive engagement). We used pre-/post- knowledge tests and multimodal learning analytics to measure students' learning outcomes and learning experiences. Results indicated that the lecture-based class utilizing HoloBoard lead to slightly better learning outcomes and a significantly higher level of student engagement. Given the results, we discussed the impact of HoloBoard as an immersive media in the classroom setting and suggest several design implications for deploying HoloBoard in immersive teaching practices., Comment: 16 pages,7 figures

Artificial Intelligence (AI), especially Neural Networks (NNs), has become increasingly popular. However, people usually treat AI as a tool, focusing on improving outcome, accuracy, and performance while paying less attention to the representation of AI itself. We present AIive, an interactive visualization of AI in Virtual Reality (VR) that brings AI "alive". AIive enables users to manipulate the parameters of NNs with virtual hands and provides auditory feedback for the real-time values of loss, accuracy, and hyperparameters. Thus, AIive contributes an artistic and intuitive way to represent AI by integrating visualization, sonification, and direct manipulation in VR, potentially targeting a wide range of audiences., Comment: 3 pages, 3 figures, 2021 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

Size and distance perception in Virtual Reality (VR) have been widely studied, albeit in a controlled laboratory setting with a small number of participants. We describe a fully remote perceptual study with a gamified protocol to encourage participant engagement, which allowed us to quickly collect high-quality data from a large, diverse participant pool (N=60). Our study aims to understand medium-field size and egocentric distance perception in real-world usage of consumer VR devices. We utilized two perceptual matching tasks -- distance bisection and size matching -- at the same target distances of 1--9 metres. While the bisection protocol indicated a near-universal trend of nonlinear distance compression, the size matching estimates were more equivocal. Varying eye-height from the floor plane showed no significant effect on the judgements. We also discuss the pros and cons of a fully remote perceptual study in VR, the impact of hardware variation, and measures needed to ensure high-quality data.