Deep Convolutional Neural Networks for Human Action Recognition Using Depth Maps and Postures
- Submitting institution
-
The University of Sheffield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 5231
- Type
- D - Journal article
- DOI
-
10.1109/tsmc.2018.2850149
- Title of journal
- IEEE Transactions on Systems, Man, and Cybernetics: Systems
- Article number
- -
- First page
- 1806
- Volume
- 49
- Issue
- 9
- ISSN
- 2168-2216
- Open access status
- Exception within 3 months of publication
- Month of publication
- July
- Year of publication
- 2019
- 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
-
5
- Research group(s)
-
E - OAK
- Citation count
- 17
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper was the first to demonstrate that state-of-the-art recognition accuracy can be obtained using a small amount of data only from front-facing cameras. The paper was listed as one of the top 50 most accessed articles by IEEE Transactions SMC for 10 months after publication.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -