Robust Deformable Shape Reconstruction from Monocular Video with Manifold Forest
- Submitting institution
-
University of Central Lancashire
- Unit of assessment
- 12 - Engineering
- Output identifier
- 14515
- Type
- D - Journal article
- DOI
-
10.1007/s00138-016-0769-3
- Title of journal
- Machine Vision and Applications
- Article number
- -
- First page
- 801
- Volume
- 27
- Issue
- 6
- ISSN
- 0932-8092
- Open access status
- Deposit exception
- Month of publication
- August
- Year of publication
- 2016
- 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
-
1
- Research group(s)
-
H - Computer Vision and Machine Learning Group
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is the final paper in a series of publications reporting on research to develop robust deformable three-dimensional structure from motion methods. The research led to the publication of six papers and completion of one PhD project. The research reported in this paper has been instrumental in securing the EPSRC funded Grant (No. EP/K019368) and supported a recently awarded STFC CDN+ grant aiming at the development of 3D mapping and navigation tools in video colonoscopy.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
