Extracting 3D parametric curves from 2D images of helical objects.
- Submitting institution
-
University of Durham
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 105327
- Type
- D - Journal article
- DOI
-
10.1109/TPAMI.2016.2613866
- Title of journal
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Article number
- -
- First page
- 1757
- Volume
- 39
- Issue
- 9
- ISSN
- 01628828
- Open access status
- Compliant
- Month of publication
- -
- Year of publication
- 2016
- URL
-
https://doi.org/10.1109/TPAMI.2016.2613866
- 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)
-
A - Innovative Computing
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- We present a method that is able to straighten the image object and derive a robust 3D helical curve from peaks in the object boundary. The algorithm has a small number of stable parameters that require little tuning, and the curve is validated against both synthetic and real-world data. Project developed in partnership with Dyson to build a mathematical model of healthy hair (Table VIIIc) to support Dyson’s new hair product line (research grant from Dyson Ltd, UK RF080296).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
