Matching non-rigidly deformable shapes across images: A globally optimal solution

While global methods for matching shapes to images have recently been proposed, so far research has focused on small deformations of a fixed template. In this paper we present the first global method able to pixel-accurately match non-rigidly deformable shapes across images at amenable run-times. By finding cycles of optimal ratio in a four-dimensional graph ? spanned by the image, the prior shape and a set of rotation angles ? we simultaneously compute a segmentation of the image plane, a matching of points on the template to points on the segmenting boundary, and a decomposition of the template into a set of deformable parts. In particular, the interpretation of the shape template as a collection of an a priori unknown number of deformable parts ? an important aspect of higher-level shape representations ? emerges as a byproduct of our matching algorithm. On real-world data of running people and walking animals, we demonstrate that the proposed method can match strongly deformed sha...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Thomas Schoenemann, Daniel Cremers
• Keywords: Computer Vision, CVPR 2008, Deformable Parts, Deformable Shapes, Prior Shape, Shape Template, Simple Shape Measures