Euclidean-distance-based canonical forms for non-rigid 3D shape retrieval
- Submitting institution
-
Cardiff University / Prifysgol Caerdydd
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 95898656
- Type
- D - Journal article
- DOI
-
10.1016/j.patcog.2015.02.021
- Title of journal
- Pattern Recognition
- Article number
- -
- First page
- 2500
- Volume
- 48
- Issue
- 8
- ISSN
- 0031-3203
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2015
- URL
-
http://dx.doi.org/10.1016/j.patcog.2015.02.021
- 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)
-
V - Visual computing
- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper addresses canonical form computation for 3D non-rigid shape retrieval, by proposing a linear time complexity method for multidimensional scaling (MDS). It reduces the average computational time by a factor of 35 compared with the current fast MDS method for meshes with an average of 9300 vertices, and can be used for higher resolution meshes. It is highlighted as an efficient approach in a literature review of the field (https://doi.org/10.1007/s11432-019-2757-1).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -