@Article{NaveenOnkarappa2013,
author="Naveen Onkarappa
and Angel Sappa",
title="A Novel Space Variant Image Representation",
journal="Journal of Mathematical Imaging and Vision",
year="2013",
publisher="Springer US",
volume="47",
number="1-2",
pages="48--59",
optkeywords="Space-variant representation",
optkeywords="Log-polar mapping",
optkeywords="Onboard vision applications",
abstract="Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences.",
optnote="ADAS; 600.055; 605.203; 601.215",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2243), last updated on Thu, 21 Jan 2016 12:30:47 +0100",
issn="0924-9907",
doi="10.1007/s10851-012-0384-5"
}