Object detection resource usage within a remote real-time video stream
Paper
Paper/Presentation Title | Object detection resource usage within a remote real-time video stream |
---|---|
Presentation Type | Paper |
Authors | Smith, Mark (Author), Maiti, Ananda (Author), Maxwell, Andrew D. (Author) and Kist, Alexander A. (Author) |
Editors | Auer, Michael E. and Zutin, Danilo G. |
Journal or Proceedings Title | Proceedings of the 14th International Conference on Remote Engineering and Virtual Instrumentation (REV 2017) |
ERA Conference ID | 50808 |
Journal Citation | 22, pp. 266-277 |
Number of Pages | 12 |
Year | 2017 |
Place of Publication | Switzerland |
ISBN | 9783319643519 |
9783319643526 | |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-319-64352-6_25 |
Web Address (URL) of Paper | https://link.springer.com/chapter/10.1007/978-3-319-64352-6_25 |
Conference/Event | 14th International Conference on Remote Engineering and Virtual Instrumentation (REV 2017): Online Engineering & Internet of Things: |
International Conference on Remote Engineering and Virtual Instrumentation | |
Event Details | 14th International Conference on Remote Engineering and Virtual Instrumentation (REV 2017): Online Engineering & Internet of Things: Event Date 15 to end of 17 Mar 2017 Event Location New York, USA |
Event Details | International Conference on Remote Engineering and Virtual Instrumentation REV |
Abstract | The growth in remote education through technologies such as Re-mote Access Laboratories has progressed to a stage where automated interpreta-tions of visual scenes within a video stream are necessary to pro-vide enhanced learning experiences. Augmented Reality tools are under development to ex-pand the current reach and immersion of remote laboratories. Network capabili-ties between the experiment host and the client can affect the level of these en-hancements. Augmented Reality relies on sensory engagement, which is criti-cally linked to the synchronization between the real-time scenes and the com-puter-generated enhancements. This work highlights the problems of incorpo-rating Augmented Reality into Remote Access Laboratories, and the methods to improve the level of user immersion. |
Keywords | remote laboratories; augmented reality; computer network; data clustering |
ANZSRC Field of Research 2020 | 460304. Computer vision |
399999. Other education not elsewhere classified | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | School of Mechanical and Electrical Engineering |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q4v38/object-detection-resource-usage-within-a-remote-real-time-video-stream
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