Video Stream Analysis in Clouds: An Object Detection and Classification Framework for High Performance Video Analytics
- Submitting institution
-
The University of Leicester
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2387
- Type
- D - Journal article
- DOI
-
10.1109/TCC.2016.2517653
- Title of journal
- IEEE Transactions on Cloud Computing
- Article number
- -
- First page
- 1152
- Volume
- 7
- Issue
- 4
- ISSN
- 2168-7161
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
https://doi.org/10.1109/TCC.2016.2517653
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 7
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is one of the first papers on edge-enhanced AI infrastructure that enables millions of data streams to be processed on the sources of data in real time, leading to significant reductions in analytics times, data transfer and storage costs. Fishbone Solutions (KTP, Gadsby, mark@fishbonesolutions.co.uk) has exploited the work for predictive maintenance of rolling stock on rail networks. Bloc Digital (KTP, Cox, keith@bloc.digital) is exploiting the work for producing augmented digital twins for quality assurance of manufacturing processes in aerospace. The Alice experiment at CERN Geneva (Chochula, peter.chochula@cern.ch) is using the work for real-time anomaly detection for detector control.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -