Dense sampling of shape interiors for improved representation.
Date of Issue2013
Electronic Imaging (2013 : Burlingame, USA)
School of Computer Engineering
Matching shapes accurately is an important requirement in various applications; the most notable of which is object recognition. Precisely matching shapes is a difficult task and is an active area of research in the computer vision community. Most shape matching techniques rely on the contour of the object to provide the object's shape properties. However, we show that using the contour alone cannot help in matching all kinds of shapes. Many objects are recognised because of their overall visual similarity, rather than just their contour properties. In this paper, we assert that modelling the interior properties of the shape can help in extracting this overall visual similarity. We propose a simple way to extract the shape's interior properties. This is done by densely sampling points from within the shape and using it to describe the shape's features. We show that using such an approach provides an effective way to perform matching of shapes that are visually similar to each other, but have vastly different contour properties.
DRNTU::Engineering::Computer science and engineering
© 2013 Society of Photo-Optical Instrumentation Engineers (SPIE). This paper was published in Proceeding of SPIE-IS & T Electronic Imaging and is made available as an electronic reprint (preprint) with permission of SPIE. The paper can be found at the following official DOI: [http://dx.doi.org/10.1117/12.2008480]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.