Realistic facial expression reconstruction for VR HMD users
- Submitting institution
-
University of Portsmouth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 15980376
- Type
- D - Journal article
- DOI
-
10.1109/TMM.2019.2933338
- Title of journal
- IEEE Transactions on Multimedia
- Article number
- -
- First page
- 730
- Volume
- 22
- Issue
- 3
- ISSN
- 1520-9210
- Open access status
- Compliant
- Month of publication
- August
- 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
-
6
- Research group(s)
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B - Computational Intelligence
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Developed with VR industry leader, Emteq, we present the first automatic system of its kind that senses and reconstructs the VR headset-user’s facial expressions with a realistic face embodiment. Electromyography sensors with robust machine learning track the user’s occluded facial muscle movements precisely and unobtrusively. Facial expressions are efficiently reconstructed and rendered in virtual scenarios with high fidelity. Applications include games, physiotherapy and rehabilitation. Funding from EPSRC (EP/N025849/1), RAE (IFS1819\9), and Emteq. A follow-on Innovate UK KTP application with Emteq is ready for submission by April 2021. Contact Emteq CTO, Dr. Charles Nduka, charles@emteq.net
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -