Q-MAF Shape Decomposition |
Rasmus Larsen, Hrafnkell Eiriksson, Mikkel B. Stegmann
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| Abstract | This paper address the problems of generating a low dimensional representation of the shape variation present in a set of shapes represented by a number of landmark points. First, we will present alternatives to the featured Least-Squares Procrustes alignment based on the L1-norm and the L-inf-norm. Second, we will define a new shape decomposition based on the Maximum Autocorrelation Factor (MAF) analysis, and investigate and compare its properties to the Principal Components Analysis (PCA). It is shown that Molgedey-Schuster algorithm for Independent Component Analysis (ICA) is equivalent to the MAF analysis. The shape MAF analysis utilises the natural order of landmark points
along shape contours. |
| Type | Conference paper [With referee] |
| Conference | Medical Image Computing and Computer-Assisted Intervention - MICCAI 2001, 4th Int. Conference, Utrecht, The Netherlands |
| Editors | Wiro J. Niessen, Max A. Viergever |
| Year | 2001 Month October Vol. 2208 pp. 837-844 |
| Publisher | Springer |
| Series | Lecture Notes in Computer Science |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Image Analysis & Computer Graphics |