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) |
International Conference on Remote Engineering and Virtual Instrumentation | |
Event Details | 14th International Conference on Remote Engineering and Virtual Instrumentation (REV 2017) Parent International Conference on Remote Engineering and Virtual Instrumentation Delivery In person Event Date 15 to end of 17 Mar 2017 Event Location New York, United States |
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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