A Batch Algorithm for Implicit Non-rigid Shape and Motion Recovery

The recovery of 3D shape and camera motion for non-rigid scenes from single-camera video footage is a very important problem in computer vision. The low-rank shape model consists in regarding the deformations as linear combinations of basis shapes. Most algorithms for reconstructing the parameters of this model along with camera motion are based on three main steps. Given point tracks and the rank, or equivalently the number of basis shapes, they factorize a measurement matrix containing all point tracks, from which the camera motion and basis shapes are extracted and refined in a bundle adjustment manner. There are several issues that have not been addressed yet, among which, choosing the rank automatically and dealing with erroneous point tracks and missing data. We introduce theoretical and practical contributions that address these issues. We propose an implicit imaging model for non-rigid scenes from which we derive non-rigid matching tensors and closure constraints. We give a no...

• Type: Conference
• Year: 2006
• Where: ECCV
• Authors: Adrien Bartoli, Søren I. Olsen
• Keywords: Basis Shapes, Camera Motion, Computer Vision, ECCV 2006, Non-rigid Matching Tensor