Comparison of sparse point distribution models

Søren Gylling Hemmingsen Erbou, Martin Vester-Christensen, Rasmus Larsen, Lars Bager Christensen, Bjarne Kjær Ersbøll

    Research output: Contribution to journalJournal articleResearchpeer-review


    This paper compares several methods for obtaining sparse and compact point distribution models suited for data sets containing many variables. These are evaluated on a database consisting of 3D surfaces of a section of the pelvic bone obtained from CT scans of 33 porcine carcasses. The superior model w.r.t. sparsity, reconstruction error and interpretability is found to be a varimax rotated model with a threshold applied to small loadings. The models describe the biological variation in the database and is used for developing robotic tools when automating labor intensive procedures in slaughterhouses.
    Original languageEnglish
    JournalMachine Vision & Applications
    Issue number6
    Pages (from-to)999-1008
    Publication statusPublished - 2010


    • Robotic Tools
    • Sparse PCA
    • Varimax
    • Point distribution models
    • Image analysis


    Dive into the research topics of 'Comparison of sparse point distribution models'. Together they form a unique fingerprint.

    Cite this