Efficient Point Cloud Pre-processing using The Point Cloud Library
- Submitting institution
-
University of South Wales / Prifysgol De Cymru
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1506337
- Type
- D - Journal article
- DOI
-
-
- Title of journal
- International Journal of Image Processing
- Article number
- -
- First page
- 63
- Volume
- 10
- Issue
- 2
- ISSN
- 1985-2304
- Open access status
- Deposit exception
- Month of publication
- June
- Year of publication
- 2016
- URL
-
https://www.cscjournals.org/manuscript/Journals/IJIP/Volume10/Issue2/IJIP-1063.pdf
- 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
-
3
- Research group(s)
-
D - Artificial Intelligence
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The significance of this paper is the new optimisation method for the pre-processing stage of the Point Cloud Library that affords operation on low power embedded devices, such as Raspberry Pi. Point cloud processing is demanding and previously was not accessible to embedded devices. An early version was presented at the IEEE IWSSIP 2015 conference. Requests have been received from various institutions (Nuziveedu Seeds Limited, PhotoMetrix, ViewPoint 3D, Impossible Labs) to have access to the code source. Elements of the research are being used by the spinoff company, Thermetrix (podium.care), producing the Podium medical device and continuing further research.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
