Frontal view gait recognition with fusion of depth features from a time of flight camera
- Submitting institution
-
University of Derby
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 784680-1
- Type
- D - Journal article
- DOI
-
10.1109/TIFS.2018.2870594
- Title of journal
- IEEE Transactions on Information Forensics and Security
- Article number
- -
- First page
- 1067
- Volume
- 14
- Issue
- 4
- ISSN
- 1556-6013
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2018
- URL
-
https://ieeexplore.ieee.org/abstract/document/8466800
- 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
-
4
- Research group(s)
-
-
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper employed a comprehensive ToF dataset of 46 and 33 subjects collected in two sessions 8 months apart, each presenting six walks with five covariates. Comparison with state-of-the-art demonstrated distinct improvements over recognition rates for all covariates outperforming counterparts and resulting in 81.0% Rank 5 recognition rate compared with a best performance of 57.7%. The improvement over state of the art demonstrated in this paper led to a successful Fundamental Research Grant funded by Ministry of Education, Malaysia, (Grant number is RACER/1/2019/ICT02/UNIMAS//2).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
