Binary Online Learned Descriptors
- Submitting institution
-
The University of Surrey
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 9003576_1
- Type
- D - Journal article
- DOI
-
10.1109/TPAMI.2017.2679193
- Title of journal
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Article number
- -
- First page
- 555
- Volume
- 40
- Issue
- 3
- ISSN
- 0162-8828
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2017
- URL
-
-
- 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
-
-
- Research group(s)
-
-
- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Although the paper focused on the development of a new descriptor for online tracking in images, the work on benchmarking has turned out to be more significant as the development of more powerful local descriptors has accelerated dramatically. Continuation of that work based on the insights of this paper led to the publication of a new benchmark (10.1109/TPAMI.2019.2915233) as a significant output from the major research projects ERC 677195-IDIU and EPSRC EP/N007743/1.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -