Saliency-directed prioritization of visual data in wireless surveillance networks
- Submitting institution
-
The University of Bradford
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 29
- Type
- D - Journal article
- DOI
-
10.1016/j.inffus.2014.07.002
- Title of journal
- Information Fusion
- Article number
- -
- First page
- 16
- Volume
- 24
- Issue
- -
- ISSN
- 1566-2535
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- URL
-
https://www.sciencedirect.com/science/article/abs/pii/S1566253514000852?via%3Dihub
- Supplementary information
-
-
- 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
-
3
- Research group(s)
-
-
- Citation count
- 38
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work presents salient motion detection-based visual data prioritization framework to cope the fragility of traditional multi-camera wire-less sensor networks. This work is published in one of the top journals and has found widespread applications in various computer vision domains. For example, an extension of this work titled “Intelligent and Energy-Efficient Data Prioritization in Green Smart Cities: Current Challenges and Future Directions” published in IEEE Transaction. Another application of this framework “Mobile-cloud assisted framework for selective encryption of medical images with steganography for resource-constrained devices” published in Multimedia Tools and Application. NRF Korea extended the grant for these techniques.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
