Finding Nemo: Deformable Object Class Modelling using Curve Matching

An image search for “clownfish” yields many photos of clownfish, each of a different individual of a different 3D shape in a different pose. Yet, to the human observer, this set of images contains enough information to infer the underlying 3D deformable object class. Our goal is to recover such a deformable object class model directly from unordered images. For classes where feature-point correspondences can be found, this is a straightforward extension of non-rigid factorization, yielding a set of 3D basis shapes to explain the 2D data. However, when each image is of a different object instance, surface texture is generally unique to each individual, and does not give rise to usable image point correspondences. We overcome this sparsity using curve correspondences (crease-edge silhouettes or class-specific internal texture edges). Even rigid contour reconstruction is difficult due to the lack of reliable correspondences. We incorporate correspondence variation into the optimi...

• Type: Conference
• Year: 2010
• Where: CVPR
• Authors: Mukta Prasad, Andrew Fitzgibbon
• Keywords: Computer Vision, CVPR 2010, Deformable Object, Deformable Object Class, Image