Title :
Bicycle chain shape models
Author :
Sommer, Svenja ; Tatu, Aditya ; Chen Chen ; Jurgensen, Dan R ; de Bruijne, Marleen ; Loog, Marco ; Nielsen, Mads ; Lauze, Francois
Author_Institution :
Dept. of Comput. Sci., Univ. of Copenhagen, Copenhagen, Denmark
Abstract :
In this paper we introduce landmark-based pre-shapes which allow mixing of anatomical landmarks and pseudo-landmarks, constraining consecutive pseudo-landmarks to satisfy planar equidistance relations. This defines naturally a structure of Riemannian manifold on these preshapes, with a natural action of the group of planar rotations. Orbits define the shapes. We develop a geodesic generalized procrustes analysis procedure for a sample set on such a preshape spaces and use it to compute principal geodesic analysis. We demonstrate it on an elementary synthetic example as well on a dataset of manually annotated vertebra shapes from x-ray. We re-landmark them consistently and show that PGA captures the variability of the dataset better than its linear counterpart, PCA.
Keywords :
computer vision; image representation; Riemannian manifold structure; anatomical landmarks; annotated vertebra shapes; bicycle chain shape models; geodesic generalized procrustes analysis; principal geodesic analysis; pseudo-landmarks; Bicycles; Biomedical imaging; Electronics packaging; Geophysics computing; Image analysis; Orbits; Principal component analysis; Shape; Spine; X-ray imaging;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops, 2009. CVPR Workshops 2009. IEEE Computer Society Conference on
Conference_Location :
Miami, FL
Print_ISBN :
978-1-4244-3994-2
DOI :
10.1109/CVPRW.2009.5204053