Annotation in 3D user interfaces such as Augmented Reality (AR) and Virtual Reality (VR) is a challenging and promising area; however, there are not currently surveys reviewing these contributions. In order to provide a survey of annotations for Extended Reality (XR) environments, we conducted a structured literature review of papers that used annotation in their AR/VR systems from the period between 2001 and 2021. Our literature review process consists of several filtering steps which resulted in 103 XR publications with a focus on annotation. We classified these papers based on the display technologies, input devices, annotation types, target object under annotation, collaboration type, modalities, and collaborative technologies. A survey of annotation in XR is an invaluable resource for researchers and newcomers. Finally, we provide a database of the collected information for each reviewed paper. This information includes applications, the display technologies and its annotator, input devices, modalities, annotation types, interaction techniques, collaboration types, and tasks for each paper. This database provides a rapid access to collected data and gives users the ability to search or filter the required information. This survey provides a starting point for anyone interested in researching annotation in XR environments.
more »
« less
ARENA: The Augmented Reality Edge Networking Architecture
Many have predicted the future of the Web to be the integration of Web content with the real-world through technologies such as Augmented Reality (AR). This has led to the rise of Extended Reality (XR) Web Browsers used to shorten the long AR application development and deployment cycle of native applications especially across different platforms. As XR Browsers mature, we face new challenges related to collaborative and multi-user applications that span users, devices, and machines. These collaborative XR applications require: (1) networking support for scaling to many users, (2) mechanisms for content access control and application isolation, and (3) the ability to host application logic near clients or data sources to reduce application latency. In this paper, we present the design and evaluation of the AR Edge Networking Architecture (ARENA) which is a platform that simplifies building and hosting collaborative XR applications on WebXR capable browsers. ARENA provides a number of critical components including: a hierarchical geospatial directory service that connects users to nearby servers and content, a token-based authentication system for controlling user access to content, and an application/service runtime supervisor that can dispatch programs across any network connected device. All of the content within ARENA exists as endpoints in a PubSub scene graph model that is synchronized across all users. We evaluate ARENA in terms of client performance as well as benchmark end-to-end response-time as load on the system scales. We show the ability to horizontally scale the system to Internet-scale with scenes containing hundreds of users and latencies on the order of tens of milliseconds. Finally, we highlight projects built using ARENA and showcase how our approach dramatically simplifies collaborative multi-user XR development compared to monolithic approaches.
more »
« less
- Award ID(s):
- 1956095
- NSF-PAR ID:
- 10346516
- Date Published:
- Journal Name:
- 2021 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)
- Page Range / eLocation ID:
- 479 to 488
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Augmented reality (AR), which overlays virtual content on top of the user’s perception of the real world, has now begun to enter the consumer market. Besides smartphone platforms, early-stage head-mounted displays such as the Microsoft HoloLens are under active development. Many compelling uses of these technologies are multi-user: e.g., inperson collaborative tools, multiplayer gaming, and telepresence. While prior work on AR security and privacy has studied potential risks from AR applications, new risks will also arise among multiple human users. In this work, we explore the challenges that arise in designing secure and private content sharing for multi-user AR. We analyze representative application case studies and systematize design goals for security and functionality that a multi-user AR platform should support. We design an AR content sharing control module that achieves these goals and build a prototype implementation (ShareAR) for the HoloLens. This work builds foundations for secure and private multi-user AR interactions.more » « less
-
Current collaborative augmented reality (AR) systems establish a common localization coordinate frame among users by exchanging and comparing maps comprised of feature points. However, relative positioning through map sharing struggles in dynamic or feature-sparse environments. It also requires that users exchange identical regions of the map, which may not be possible if they are separated by walls or facing different directions. In this paper, we present Cappella11Like its musical inspiration, Cappella utilizes collaboration among agents to forgo the need for instrumentation, an infrastructure-free 6-degrees-of-freedom (6DOF) positioning system for multi-user AR applications that uses motion estimates and range measurements between users to establish an accurate relative coordinate system. Cappella uses visual-inertial odometry (VIO) in conjunction with ultra-wideband (UWB) ranging radios to estimate the relative position of each device in an ad hoc manner. The system leverages a collaborative particle filtering formulation that operates on sporadic messages exchanged between nearby users. Unlike visual landmark sharing approaches, this allows for collaborative AR sessions even if users do not share the same field of view, or if the environment is too dynamic for feature matching to be reliable. We show that not only is it possible to perform collaborative positioning without infrastructure or global coordinates, but that our approach provides nearly the same level of accuracy as fixed infrastructure approaches for AR teaming applications. Cappella consists of an open source UWB firmware and reference mobile phone application that can display the location of team members in real time using mobile AR. We evaluate Cappella across mul-tiple buildings under a wide variety of conditions, including a contiguous 30,000 square foot region spanning multiple floors, and find that it achieves median geometric error in 3D of less than 1 meter.more » « less
-
Permission-based access control enables users to manage and control their sensitive data for third-party applications. In an ideal scenario, third-party application includes enough details to illustrate the usage of such data, while the reality is that many descriptions of third-party applications are vague about their security or privacy activities. As a result, users are left with insufficient details when granting sensitive data to these applications. Prior works, such as WHYPER and AutoCog, have addressed the aforementioned problem via a so-called permission correlation system. Such a system correlates third-party applications' description with their requested permissions and determines an application as overprivileged if a mismatch is found. However, although prior works are successful on their own platforms, such as Android eco-system, they are not directly applicable to new platforms, such as Chrome extensions and IFTTT, without extensive data labeling and parameter tuning. In this paper, we design, implement, and evaluate a novel system, called TKPERM, which transfers knowledges of permission correlation systems across platforms. Our key idea is that these varied platforms with different use cases---like smartphones, IoTs, and desktop browsers---are all user-facing and thus allow the knowledges to be transferrable across platforms. Particularly, we adopt a greedy selection algorithm that picks the best source domains to transfer to the target permission on a new platform. TKPERM achieves 90.02% overall F1 score after transfer, which is 12.62% higher than the one of a model trained directly on the target domain without transfer. Particularly, TKPERM has 91.83% F1 score on IFTTT, 89.13% F1 score on Chrome-Extension, and 89.1% F1 score on SmartThings. TKPERM also successfully identified many real-world overprivileged applications, such as a gaming hub requesting location permissions without legitimate use.more » « less
-
Mobile Augmented Reality (AR), which overlays digital content on the real-world scenes surrounding a user, is bringing immersive interactive experiences where the real and virtual worlds are tightly coupled. To enable seamless and precise AR experiences, an image recognition system that can accurately recognize the object in the camera view with low system latency is required. However, due to the pervasiveness and severity of image distortions, an effective and robust image recognition solution for mobile AR is still elusive. In this paper, we present CollabAR, an edge-assisted system that provides distortion-tolerant image recognition for mobile AR with imperceptible system latency. CollabAR incorporates both distortion-tolerant and collaborative image recognition modules in its design. The former enables distortion-adaptive image recognition to improve the robustness against image distortions, while the latter exploits the `spatial-temporal' correlation among mobile AR users to improve recognition accuracy. We implement CollabAR on four different commodity devices, and evaluate its performance on two multi-view image datasets. Our evaluation demonstrates that CollabAR achieves over 96% recognition accuracy for images with severe distortions, while reducing the end-to-end system latency to as low as 17.8ms for commodity mobile devices.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ISMAR52148.2021.00065
