Bootstrapping is the process of improving the performance of a trained classifier by iteratively adding data that is labeled by the classifier itself to the training set, and retr...
—This paper develops a novel surface fitting scheme for automatically reconstructing a genus-0 object into a continuous parametric spline surface. A key contribution for making ...
The observation models in tracking algorithms are critical to both tracking performance and applicable scenarios but are often simplified to focus on fixed level of certain target...
A general methodology for noise reduction and contrast enhancement in very noisy image data with low dynamic range is presented. Video footage recorded in very dim light is especi...
Henrik Malm, Magnus Oskarsson, Eric Warrant, Petri...
We describe a method for automatically and adaptively boosting the visibility of local features in an image. A log intensity image is first decomposed into a set of subbands at mu...