@CONFERENCE\{IMM2001-0117,
    author       = "R. Larsen and H. Eiriksson and M. B. Stegmann",
    title        = "{Q-MAF} Shape Decomposition",
    year         = "2001",
    month        = "oct",
    pages        = "837-844",
    booktitle    = "Medical Image Computing and Computer-Assisted Intervention - {MICCAI} 2001, 4th Int. Conference, Utrecht, The Netherlands",
    volume       = "2208",
    series       = "Lecture Notes in Computer Science",
    editor       = "Wiro J. Niessen, Max A. Viergever",
    publisher    = "Springer",
    organization = "",
    address      = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/117-full.html",
    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."
}