We propose the concept of relative translation gains, a novel Redirected Walking (RDW) method to create a mutual movable space between the Augmented Reality (AR) host's reference space and the Virtual Reality (VR) client's space. Previous RDW methods have focused on maximizing the movable space at the expense of aligning the coordinates between the AR and VR side, and could only be applied to collaborative scenarios involving sequential tasks. Our method solves these problems by adjusting the remote client's walking speed for each axis of a VR space to modify the movable area without coordinate distortion. We estimate the relative translation gain threshold, defined as the extent to which the walking speed can be altered without creating a perceived difference in distance. In order to reflect features of the reference space in generating the mutual space, we then examine how changing its size affects the threshold value. Our study showed that for remote clients connected to the larger reference space, relative translation gains can be increased to utilize a VR space bigger than their real space. Our method can be applied to create optimal mutual spaces for a wider variety of asymmetric Mixed Reality (MR) remote collaboration systems.

Adjusting Relative Translation Gains According to Space Size in Redirected Walking for Mixed Reality Mutual Space Generation

Mixed Reality allows for distributed meetings where people’s local physical spaces are virtually aligned into blended interaction spaces. In many cases, people’s physical rooms are dissimilar, making it challenging to design a coherent blended space. We introduce the concept of Partially Blended Realities (PBR) — using Mixed Reality to support remote collaborators in partially aligning their physical spaces. As physical surfaces are central in collaborative work, PBR supports users in transitioning between different configurations of tables and whiteboard surfaces. In this paper, we 1) describe the design space of PBR, 2) present RealityBlender to explore interaction techniques for how users may configure and transition between blended spaces, and 3) provide insights from a study on how users experience transitions in a remote collaboration task. With this work, we demonstrate new potential for using partial solutions to tackle the alignment problem of dissimilar spaces in distributed Mixed Reality meetings.

https://dl.acm.org/doi/pdf/10.1145/3544548.3581515

Partially Blended Realities: Aligning Dissimilar Spaces for Distributed Mixed Reality Meetings

Human territories: How we behave in space-time.

Research on Extended Reality (XR) and Artificial Intelligence (AI) is booming, which has led to an emerging body of literature in their intersection. However, the main topics in this intersection are unclear, as are the benefits of combining XR and AI. This paper presents a scoping review that highlights how XR is applied in AI research and vice versa. We screened 2619 publications from 203 international venues published between 2017 and 2021, followed by an in-depth review of 311 papers. Based on our review, we identify five main topics at the intersection of XR and AI, showing how research at the intersection can benefit each other. Furthermore, we present a list of commonly used datasets, software, libraries, and models to help researchers interested in this intersection. Finally, we present 13 research opportunities and recommendations for future work in XR and AI research.

/pdf/when-xr-and-ai-meet-a-scoping-review-on-extended-reality-and-3a894xxc.pdf

When XR and AI Meet - A Scoping Review on Extended Reality and Artificial Intelligence

Augmented reality (AR) can create the illusion of being virtually co-located during remote collaboration, e.g., by visualizing remote co-workers as avatars. However, spatial awareness of each other's activities is limited as physical spaces, including the position of physical devices, are often incongruent. Therefore, alignment methods are needed to support activities on physical devices. In this paper, we present the concept of Re-locations, a method for enabling remote collaboration with augmented reality in incongruent spaces. The idea of the concept is to enrich remote collaboration activities on multiple physical devices with attributes of co-located collaboration such as spatial awareness and spatial referencing by locally relocating remote user representations to user-defined workspaces. We evaluated the Re-locations concept in an explorative user study with dyads using an authentic, collaborative task. Our findings indicate that Re-locations introduce attributes of co-located collaboration like spatial awareness and social presence. Based on our findings, we provide implications for future research and design of remote collaboration systems using AR.

/pdf/re-locations-augmenting-personal-and-shared-workspaces-to-1pz2irj9.pdf

Re-locations: Augmenting Personal and Shared Workspaces to Support Remote Collaboration in Incongruent Spaces

Rapidly developing technologies are realizing a 3D telepresence, in which geographically separated users can interact with each other through their virtual avatars. In this paper, we present novel methods to determine the avatar's position in an indoor space to preserve the semantics of the user's position in a dissimilar indoor space with different space configurations and furniture layouts. To this end, we first perform a user survey on the preferred avatar placements for various indoor configurations and user placements, and identify a set of related attributes, including interpersonal relation, visual attention, pose, and spatial characteristics, and quantify these attributes with a set of features. By using the obtained dataset and identified features, we train a neural network that predicts the similarity between two placements. Next, we develop avatar placement method that preserves the semantics of the placement of the remote user in a different space as much as possible. We show the effectiveness of our methods by implementing a prototype AR-based telepresence system and user evaluations.

Placement Retargeting of Virtual Avatars to Dissimilar Indoor Environments.

We present a novel mixed reality (MR) telepresence system, which enables a local user to interact with a remote user through full-body avatars in their own rooms. If the remote rooms have different size and furniture arrangement, directly applying the user’s motion to the avatar leads to mismatch of placement and deictic gesture. To overcome this problem, we retarget the placement, arm gesture and head movement of the local user to the avatar in remote room to preserve the environment and interaction context of the local user. This allows avatars to utilize real furniture and interact with the local user and shared objects as if they were in the same room.

A Mixed Reality Telepresence System for Dissimilar Spaces Using Full-Body Avatar

We present a novel mixed reality (MR) telepresence system enabling a local user to interact with a remote user through full-body avatars in their own rooms. If the remote rooms have different sizes and furniture arrangements, directly applying a user's motion to an avatar leads to a mismatch of placement and deictic gesture. To overcome this problem, we retarget the placement, arm gesture, and head movement of a local user to an avatar in a remote room to preserve a local user's environment and interaction context. This allows avatars to utilize real furniture and interact with a local user and shared objects as if they were in the same room. This paper describes our system's design and implementation in detail and a set of example scenarios in the living room and office room. A qualitative user study delves into a user experience, challenges, and possible extensions of the proposed system.

A Full Body Avatar-Based Telepresence System for Dissimilar Spaces.

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Placement Retargeting of Virtual Avatars to Dissimilar Indoor Environments.

A Mixed Reality Telepresence System for Dissimilar Spaces Using Full-Body Avatar

A Full Body Avatar-Based Telepresence System for Dissimilar Spaces.