This course covers the image foresting transform and its applications
in all steps of an image processing and analysis pipeline: filtering,
segmentation, description and categorization.
The most recent talk about the IFT with pointers to the key works
in the past 10 years and applications involving object tracking, image
segmentation (interative and automatic --- segmentation based on cloud
bank model) and patter recognition systems in biometry, remote
sensing, and biomedical data analysis. This lecture was presented at
the 16th International Conference on Digital Signal Processing in
2009. The following videos were presented during the talk.
This lecture reviews previous works on the IFT and presents its
extension from the image domain to the feature space, where
optimum-path forest classifiers can be projected. This talk was
presented at the 8th International Symposium on Mathematical Morphology in
2007, at ESIEE in 2008 and at the University of Minnesota in 2008.
First lecture that introduces the Image Foresting Transform (IFT) and
presents its use in the design of image processing operators. This
talk was presented at the University of Iowa and University of
Pennsylvania in 2004.
Last time this page was updated and we remembered to update this line:Jul 14th, 2009