Making Sense of Doppler Effect for Multi-Modal Hand Motion Detection
- Submitting institution
-
University of Exeter
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6409
- Type
- D - Journal article
- DOI
-
10.1109/TMC.2017.2762677
- Title of journal
- IEEE Trans. Mob. Comput.
- Article number
- -
- First page
- 2087
- Volume
- 17
- Issue
- 9
- ISSN
- 1536-1233
- Open access status
- Technical exception
- Month of publication
- October
- 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
-
5
- Research group(s)
-
-
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper describes AudioGest, the first device-free gestures recognition system, for consumer electronic devices, of its kind. It was invited for oral presentation at the UbiComp conference, formed an important part of Australian Research Council (ARC) Discovery project, Learning Human Activities through Low Cost, Unobtrusive RFID Technology, and was reported by The Australian newspaper. AudioGest was a foundation for the Digital Health CRC ($200 Million), Australian Commonwealth Government Cooperative Research Centres Program. It was part of the author's PhD thesis, which received the Doctoral Thesis Excellence Award from The University of Adelaide
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -