SceneCam: Using AR to improve Multi-Camera Remote Collaboration

Rasmussen, Troels; Huang, Weidong

doi:10.1145/3355355.3361892

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…SceneCam [79,80] was a multi-camera remote collaboration system that allowed a remote user to have multiple views of the task space. The local user wore an AR HMD that collected information about the local space and ran an algorithm that determined which camera view captured his actions the best.…”

Section: Augmented Reality (Ar)mentioning

confidence: 99%

A Review on Methods and Systems for Remote Collaboration

et al. 2021

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Due to the appearance of COVID-19 in 2019, person-to-person interactions were drastically reduced. The impact of these restrictions on the economic environment was significant. For example, technical assistance for commissioning or adjusting the parameters of some complex machines/installations had to be postponed. Economic operators became interested in the possibility of remote collaboration, depending on the manufactured products and the performance of the production lines that they owned. This bibliographic research was undertaken to address these needs. The purpose of this review was to analyze the current solutions, approaches, and technologies that workers and specialists can implement to obtain a reliable remote collaboration system. This survey focuses on techniques, devices, and tools that are being used in different contexts to provide remote guidance. We present communication cues and methods being employed, the implemented technological support, and the areas that benefit from remote collaboration. We hope that our effort will be useful to those who develop such systems and people who want to learn about the existence of collaborative solutions, and that it will increase awareness about the applications and the importance of the domain. We are convinced that, with the development of communication systems, the advancement of remote support systems will be a goal for many economic operators.

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Section: Augmented Reality (Ar)mentioning

confidence: 99%

A Review on Methods and Systems for Remote Collaboration

et al. 2021

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“…Users engaged in their AR-mediated physical surroundings are encouraged to accomplish tasks in co-facilitated environments with shared and collaborative AR experiences amongst multiple users [144]. Multiple dimensions of AR collaborative UIs are discussed throughout various applications, for instance, working [144,218] and playful [61,123] contents, local/co-located [170] and remote [196] users, sole AR [144,170] and a mixture of AR and VR [61,182], co-creation/coediting by multiple users (i.e., multiple users at the front of AR scenes) [144,170], supported and guided instruction (i.e., multiple users connecting to one user at the front of AR scenes) [47,61], human-to-human interactions [123,144,170], and the interaction between human and AR bots, such as tangible robots [174] and digital agent representatives [17].…”

Section: Collaborative Uis In Multi-user and Multi-device Armentioning

confidence: 99%

“…Multi-user collaborative environments has been a research topic in the domain of humancomputer interaction, which has evolved from sedentary desktop computers [221] to mobile devices and head-worn computers [61,144,196,218]. The success of such collaborative environments needs to cope with several design challenges, including (1) high awareness of others' actions and intentions, (2) high control over the interface, (3) high availability of background information, (4) information transparency amongst collaborators, and (5) information transparency whilst not affecting other users [38,263].…”

Section: Collaborative Uis In Multi-user and Multi-device Armentioning

confidence: 99%

Mobile Augmented Reality: User Interfaces, Frameworks, and Intelligence

Cao,

Lam,

Lee

et al. 2021

Preprint

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Mobile Augmented Reality (MAR) integrates computer-generated virtual objects with physical environments for mobile devices. MAR systems enable users to interact with MAR devices, such as smartphones and headworn wearables, and performs seamless transitions from the physical world to a mixed world with digital entities. These MAR systems support user experiences by using MAR devices to provide universal accessibility to digital contents. Over the past 20 years, a number of MAR systems have been developed, however, the studies and design of MAR frameworks have not yet been systematically reviewed from the perspective of user-centric design. This article presents the first effort of surveying existing MAR frameworks (count: 37) and further discusses the latest studies on MAR through a top-down approach: (1) MAR applications; (2) MAR visualisation techniques adaptive to user mobility and contexts; (3) systematic evaluation of MAR frameworks including supported platforms and corresponding features such as tracking, feature extraction plus sensing capabilities; and (4) underlying machine learning approaches supporting intelligent operations within MAR systems. Finally, we summarise the development of emerging research fields, current state-of-the-art, and discuss the important open challenges and possible theoretical and technical directions. This survey aims to benefit both researchers and MAR system developers alike. CCS Concepts: • Human-centered computing → Mixed / augmented reality; Graphical user interfaces; • Software and its engineering → Development frameworks and environments; • Computing methodologies → Machine learning approaches.

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