A fast approach to deformable surface 3D tracking
Deformable surface 3D tracking is a severely under-constrained problem and great efforts have been made to solve it. A recent state-of-the-art approach solves this problem by formulating it as a second order cone programming (SOCP) problem. However, one drawback of this approach is that it is time-consuming. In this paper, we propose an effective method for 3D deformable surface tracking. First, we formulate the deformable surface tracking problem as a linear programming (LP) problem. Then, we solve the LP problem with an algorithm which converges superlinearly rather than bisection algorithm whose convergence speed is linear. Our experimental studies on synthetic and real data have demonstrated the proposed method can not only reliably recover 3D structures of surfaces but also run faster than the state-of-the-art method.
linear programming deformable surface 3d reconstruction convex optimization