Research outputs per year
Research outputs per year
Project Details
Description
Recognizing human activities is a long standing research problem. A commonly found approach makes use of the various sensors available on mobile phones or similar devices. More recently, there has been a push to develop techniques that are not dependent on a person carrying a device. The aim of this project was to investigate and develop novel computer vision techniques to aid in the recognition of activities. Potential applications include assisted living applications.
| Status | Finished |
|---|---|
| Effective start/end date | 8/03/17 → 2/09/19 |
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Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
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Multi-view region-adaptive multi-temporal DMM and RGB action recognition
Al-Faris, M. M. N., Chiverton, J., Yang, L. & Ndzi, D., 21 Apr 2020, (Early online) In: Pattern Analysis & Applications. 16 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile173 Downloads (Pure) -
Deep learning of fuzzy weighted multi-resolution depth motion maps with spatial feature fusion for action recognition
Al-Faris, M. M. N., Chiverton, J., Yang, L. & Ndzi, D., 21 Oct 2019, In: Journal of Imaging. 5, 10, 25 p., 82.Research output: Contribution to journal › Article › peer-review
Open AccessFile178 Downloads (Pure) -
Appearance and motion information based human activity recognition
Al-Faris, M. M. N., Chiverton, J., Yang, L. & Ndzi, D., 21 May 2018, IET 3rd International Conference on Intelligent Signal Processing (ISP 2017). London, UK: IET Conference Publications, p. 1-6 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile163 Downloads (Pure)