@TECHREPORT\{IMM2002-0922,
    author       = "M. B. Stegmann",
    title        = "Analysis and Segmentation of Face Images using Point Annotations and Linear Subspace Techniques",
    year         = "2002",
    month        = "aug",
    keywords     = "shape analysis, generative modelling, face recognition, active shape models, active appearance models, annotated image data set",
    pages        = "25",
    number       = "",
    series       = "",
    institution  = "Informatics and Mathematical Modelling, Technical University of Denmark, {DTU}",
    address      = "Richard Petersens Plads, Building 321, {DK-}2800 Kgs. Lyngby",
    type         = "",
    note         = "See the publication link for the images and the annotations.",
    url          = "http://www.imm.dtu.dk/~aam/datasets/face_data.zip",
    abstract     = "This report provides an analysis of 37 annotated frontal face images. All results presented have been obtained using our freely available Active Appearance Model (AAM) implementation. To ensure the reproducibility of the presented experiments, the data set has also been made available. As such, the data and this report may serve as a point of reference to compare other {AAM} implementations against. 
In addition, we address the problem of {AAM} model truncation using parallel analysis along with a comparable study of the two prevalent {AAM} learning methods; principal component regression and estimation of fixed Jacobian matrices.
To assess applicability and efficiency, timings for model building, warping and optimisation are given together with a description of how to exploit the warping capabilities of contemporary consumer-level graphics hardware.",
    isbn_issn    = "IMM-REP-2002-22"
}