Abstract book (pdf) - ICPR 2010

15:50-16:10, Paper MoBT3.2
Estimating Nonrigid Shape Deformation using Moments
Liu, Wei, Florida Inst. of Tech.
Ribeiro, Eraldo, Florida Inst. of Tech.
Image moments have been widely used for designing robust shape descriptors that are invariant to rigid transformations.
In this work, we address the problem of estimating non-rigid deformation fields based on image moment variations. By
using a single family of polynomials to both parameterize the deformation field and to define image moments, we can
represent image moments variation as a system of quadratic functions, and solve for the deformation parameters. As a
result, we can recover the deformation field between two images without solving the correspondence problem. Additionally,
our method is highly robust to image noise. The method was tested on both synthetically deformed MPEG-7 shapes and
cardiac MRI sequences.
16:10-16:30, Paper MoBT3.3
Optical Flow Estimation using Diffusion Distances
Wartak, Szymon, Univ. of York
Bors, Adrian, Univ. of York
In this paper we apply the diffusion framework to dense optical flow estimation. Local image information is represented
by matrices of gradients between paired locations. Diffusion distances are modelled as sums of eigenvectors weighted by
their eigenvalues extracted following the eigen decomposion of these matrices. Local optical flow is estimated by correlating
diffusion distances characterizing features from different frames. A feature confidence factor is defined based on
the local correlation efficiency when compared to that of its neighbourhood. High confidence optical flow estimates are
propagated to areas of lower confidence.
16:30-16:50, Paper MoBT3.4
Novel Multi View Structure Estimation based on Barycentric Coordinates
Ruether, Matthias, Graz Univ. of Tech.
Bischof, Horst, Graz Univ. of Tech.
Traditionally, multi-view stereo algorithms estimate three-dimensional structure from corresponding points by linear triangulation
or bundle-adjustment. This introduces systematic errors in case of inaccurate camera calibration and partial
occlusion. The errors are not negligible in applications requiring high accuracy like micro-metrology or quality inspection.
We show how accuracy of structure estimation can be significantly increased by using a barycentric coordinate representation
for central perspective projection. Experiments show a reduction of geometric error by 50% compared with bundle
adjustment. The error remains almost constantly low, even under partial occlusion.
16:50-17:10, Paper MoBT3.5
Estimation of Non-Rigid Surface Deformation using Developable Surface Model
Watanabe, Yoshihiro, Univ. of Tokyo
Nakashima, Takashi, Univ. of Tokyo
Komuro, Takashi, Univ. of Tokyo
Ishikawa, Masatoshi, Univ. of Tokyo
There is a strong demand for a method of acquiring a non-rigid shape under deformation with high accuracy and high resolution.
However, this is difficult to achieve because of performance limitations in measurement hardware. In this paper,
we propose a model based method for estimating non-rigid deformation of a developable surface. The model is based on
geometric characteristics of the surface, which are important in various applications. This method improves the accuracy
of surface estimation and planar development from a low-resolution point cloud. Experiments using curved documents
showed the effectiveness of the proposed method.
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