Moving Object Detection using Adaptive Blind Update and RGB-D Camera
- Submitting institution
-
Brunel University London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 074-204785-5956
- Type
- D - Journal article
- DOI
-
10.1109/JSEN.2019.2920515
- Title of journal
- Ieee Sensors Journal
- Article number
- -
- First page
- 1
- Volume
- 19
- Issue
- 18
- ISSN
- 1530-437X
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2019
- URL
-
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8732428
- 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
-
2
- Research group(s)
-
2 - Software, Systems & Security (SSS)
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Published in one of the leading IEEE journals, the work produces a robust solution for handling camouflage in order to identify objects in dynamic scenes. The proposed algorithm can be used to control drones in difficult environments without any previous training, which has the capacity to influence the development of solutions for system to be controlled in hazardous locations. The algorithm has been shown to outperform some of the state-of-the-art algorithms in the field.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
