@CONFERENCE\{IMM1997-01117,
    author       = "R. Larsen",
    title        = "Estimation of Centers and Stagnation points in optical flow fields",
    year         = "1997",
    keywords     = "optical flow, stagnation points",
    booktitle    = "Proceedinsg of the 6th Danisk Conference on Pattern Recognition and Image Analysis ({DANKOMB,} {DSAGM} yearly meeting), Aug.",
    volume       = "",
    series       = "{DIKU} Rapport 97/",
    editor       = "Peter Johansen",
    publisher    = "Dept. of Computer Science (DIKU), University of Copenhagen",
    organization = "",
    address      = "Universitetsparken {1,} {DK-}2100 K{\o}benhavn {\O}",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/1117-full.html",
    abstract     = "In a topological sense fluid flows are characterised by their stagnation
points. Given a temporal sequence of images of fluids we will consider the
application of local polynomials to the estimation of smooth fluid flow fields.
The normal flow at intensity contours is estimated from the local
distribution of spatio-temporal energy, which is sampled using a set of
spatio-temporal quadrature filters. These observations of normal flows are
then integrated into smooth flow fields by locally approximating
first order polynomials in the spatial coordinates to the flow vectors.
This technique furthermore allows us to give a qualitative local description
of the flow field and to estimate the position of stagnation points
(e.g. nodes, saddles, and centers).
We will apply the algorithm to two data sets. The first sequence consists of
infrared images from the meteorological satellite Meteosat. Here the purpose is
that of estimating cloud motion. The second sequence visualises the airflow in
a model of a livestock building by inducing smoke in the air inlets and
illuminating a plane using a laser sheet. In this case the task is to
estimate the flow field in order to evaluate the ventilation system.",
    isbn_issn    = "{ISSN} 0107-8283"
}