Search for dissertations about: "Grassmann manifold."

Found 3 swedish dissertations containing the words Grassmann manifold..

  2. 1. Stochastic Modeling for Video Object Tracking and Online Learning: manifolds and particle filters

    Author : Zulfiqar Hasan Khan; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; anisotropic mean shift; online learning of reference object; covariance tracking; consensus point feature correspondences; Bayesian tracking; Gabor features; Visual object tracking; Grassmann manifold.; Riemannian manifold; particle filters;

    Abstract : Classical visual object tracking techniques provide effective methods when parameters of the underlying process lie in a vector space. However, various parameter spaces commonly occurring in visual tracking violate this assumption. READ MORE

  4. 2. Subspace Computations via Matrix Decompositions and Geometric Optimization

    Author : Lennart Simonsson; Axel Ruhe; Linköpings universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Mathematics; Numerical Analysis; Rank-revealing UTV; Jacobi-Davidson algorithm; Decomposition; Grassmann type algorithms; Numerical analysis; Numerisk analys;

    Abstract : This thesis is concerned with the computation of certain subspaces connected to a given matrix, where the closely related problem of approximating the matrix with one of lower rank is given special attention. To determine the rank and obtain bases for fundamental subspaces such as the range and null space of a matrix, computing the singular value decomposition (SVD) is the standard method. READ MORE

  5. 3. Projection Techniques for Classification and Identification

    Author : David Lindgren; Lennart Ljung; Linköpings universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

    Abstract : It is very well understood how to evaluate and find, in different senses, optimal linear projections of measurements on linear systems. The solution to the linear least squares problem, the principal component analysis and partial least squares are all examples of well known techniques that work very well as long as the dependencies in data are fairly linear. READ MORE