Arvind Nayak

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An important challenge of any skin color based tracking system is to accommodate varying illumination conditions. We present a method for automatic transformation of the color planes to match the skin color model learnt for a fixed illumination. The first couple of initial frames are used to automatically extract the palm region which in turn serves as an(More)
A variety of least-squares estimators of significantly different complexity and generality are available to solve over-constrained linear systems. The most theoretically general may not necessarily be the best choice in practice; problem conditions may be such that simpler and faster algorithms, if theoretically inferior, would yield acceptable errors. We(More)
A novel appearance-based simulator of burst illumination laser sequences, SimBIL, is presented and the sequences it generates are compared with those of a physical model-based simulator that the authors have developed concurrently. SimBIL uses a database of 3D, geometric object models as faceted meshes, and attaches example-based representations of material(More)
Several computer vision problems lead to linear systems affected by noise. These are commonly solved by least-squares estimators, the most popular being ordinary least squares (LS), total least squares (TLS) and generalized total least squares (GTLS). However, the statistical or structural assumptions of these theoretical estimators are very often violated(More)
Varying illumination conditions result in images of a same scene differing widely in color and contrast. Accommodating such images is a problem ubiquitous in machine vision systems. A general approach is to map colors (or features extracted from colors within some pixel neighborhood) from a source image to those in some target image acquired under canonical(More)
The Mauritius Radio Telescope (MRT) images show systemat-ics in the positional errors of sources when compared to source positions in the Molonglo Reference Catalogue (MRC). We have applied two-dimensional homog-raphy to correct positional errors in the image domain and avoid reprocessing the visibility data. Positions of bright (above 15-σ) sources, common(More)
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