Title :
Symmetric Shape Completion Under Severe Occlusions
Author :
Venkatesh, M.V. ; Cheung, S.S.
Author_Institution :
Center for Visualization & Virtual Environ., Kentucky Univ., Lexington, KY, USA
Abstract :
In this paper, we propose a novel algorithm for completing rotationally symmetrical shapes under severe occlusions. The intuitive idea is to use the existing contour, under a carefully estimated similarity transform, to fill in the missing portion of a symmetric object due to occlusions. Our algorithm exploits the invariant nature of the curvature under similarity transform and the periodicity of the curvature of a symmetric object contour. To arrive at the appropriate transform, we first estimate the fundamental period in the curvature. We use the fundamental period and the harmonic components to estimate the fundamental angle of rotation and the centroid of the unoccluded shape, which in turn establish different modes of symmetry. By following each mode of symmetry we compute the corresponding transform and select the ones that best complete the missing portion of the contour.
Keywords :
image reconstruction; object detection; transforms; fundamental angle estimation; harmonic component; occlusion; shape completion; similarity transform; symmetric object contour; Application software; Computer vision; Data visualization; Image analysis; Image reconstruction; Interpolation; Machine vision; Object recognition; Shape measurement; Virtual environment; Image shape analysis; Interpolation;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.312439