2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) 2020
DOI: 10.1109/percomworkshops48775.2020.9156256
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Invited Paper: Edge-based Provisioning of Holographic Content for Contextual and Personalized Augmented Reality

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Cited by 8 publications
(4 citation statements)
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“…The effectiveness of edge intelligence primarily depends on (i) the volume of data transmitted for communication between the User device and edge computing and (ii) the required data processing time at edge computing [41]. Since edge computing is located near the data source, quick data transfer and ensures low latency [42]. Additionally, edge computing ensures Quality of Service (QoS) even with large amounts of data [43].…”
Section: ) Edge Intelligencementioning
confidence: 99%
“…The effectiveness of edge intelligence primarily depends on (i) the volume of data transmitted for communication between the User device and edge computing and (ii) the required data processing time at edge computing [41]. Since edge computing is located near the data source, quick data transfer and ensures low latency [42]. Additionally, edge computing ensures Quality of Service (QoS) even with large amounts of data [43].…”
Section: ) Edge Intelligencementioning
confidence: 99%
“…For example, in [178] we developed a system to predict the quality of virtual content positioning (a function of AR device pose estimate error) from environment properties, in which we transmitted data collected on the AR device to the edge for the computationally expensive pre-processing and model inference. In [114] we presented an edge-assisted collaborative image recognition system, in [179] we demonstrated an edge-supported AR application that analyzed user eye movements to recognize common activities in a museum scenario, and we have developed multiple systems that provide edge-based provisioning of contextual virtual content [63]. We see the incorporation of IoT devices that provide additional contextual data as a natural extension to these edge architectures for context-aware AR, and we recently presented an example of this in [177] (see Section 5.1 for further details).…”
Section: Edge Computing For Armentioning
confidence: 99%
“…The synchronization of data streams from multiple cameras or sensors and that of audiovisual and haptic information in data transmission also create new challenges. The storing and processing of massive data for immersive communications demand new architectures and techniques for caching and computing (Glushakov et al, 2020;Taleb et al, 2021). Moreover, artificial intelligence (AI) is necessary both for supporting applications such as human-machine collaboration and user viewpoint/gesture prediction, and for orchestrating network resources to satisfy the demanding requirements of immersive communications (Maier et al, 2018;Tataria et al, 2021;Zawish et al, 2022).…”
Section: Introductionmentioning
confidence: 99%