Title :
Convex Optimization for Deformable Surface 3-D Tracking
Author :
Salzmann, Mathieu ; Hartley, Richard ; Fua, Pascal
Abstract :
3-D shape recovery of non-rigid surfaces from 3-D to 2-D correspondences is an under-constrained problem that requires prior knowledge of the possible deformations. State-of-the-art solutions involve enforcing smoothness constraints that limit their applicability and prevent the recovery of sharply folding and creasing surfaces. Here, we propose a method that does not require such smoothness constraints. Instead, we represent surfaces as triangulated meshes and, assuming the pose in the first frame to be known, disallow large changes of edge orientation between consecutive frames, which is a generally applicable constraint when tracking surfaces in a 25 frames- per-second video sequence. We will show that tracking under these constraints can be formulated as a Second Order Cone Programming feasibility problem. This yields a convex optimization problem with stable solutions for a wide range of surfaces with very different physical properties.
Keywords :
convex programming; image sequences; mesh generation; optical tracking; pose estimation; surface fitting; video signal processing; 3D shape recovery; convex optimization; deformable 3D surface tracking; edge orientation; second order cone programming feasibility problem; triangulated mesh; video sequence; Australia; Deformable models; Government; Learning systems; Linearity; Manifolds; Plastics; Shape; Surface reconstruction; Video sequences;
Conference_Titel :
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location :
Rio de Janeiro
Print_ISBN :
978-1-4244-1630-1
Electronic_ISBN :
1550-5499
DOI :
10.1109/ICCV.2007.4409031