PatchMatch Belief Propagation for Correspondence Field Estimation and its Applications

Correspondence fields estimation is an important process that lies at the core of many different applications. Is it often seen as an energy minimisation problem, which is usually decomposed into the combined minimisation of two energy terms. The first is the unary energy, or data term, which reflects how well the solution agrees with the data. The second is the pairwise energy, or smoothness term, and ensures that the solution displays a certain level of smoothness, which is crucial for many applications. This thesis explores the possibility of combining two well-established algorithms for correspondence field estimation, PatchMatch and Belief Propagation, in order to benefit from the strengths of both and overcome some of their weaknesses. Belief Propagation is a common algorithm that can be used to optimise energies comprising both unary and pairwise terms. It is however computational expensive and thus not adapted to continuous spaces which are often needed in imaging applications. On the other hand, PatchMatch is a simple, yet very efficient method for optimising the unary energy of such problems on continuous and high dimensional spaces. The algorithm has two main components: the update of the solution space by sampling and the use of the spatial neighbourhood to propagate samples. We show how these components are related to the components of a specific form of Belief Propagation, called Particle Belief Propagation (PBP). PatchMatch however suffers from the lack of an explicit smoothness term. We show that unifying the two approaches yields a new algorithm, PMBP, which has improved performance compared to PatchMatch and is orders of magnitude faster than PBP. We apply our new optimiser to two different applications: stereo matching and optical flow. We validate the benefits of PMBP through series of experiments and show that we consistently obtain lower errors than both PatchMatch and Belief Propagation

Cooperative patch-based 3D surface tracking

This paper presents a novel dense motion capture technique which creates a temporally consistent mesh sequence from several calibrated and synchronised video sequences of a dynamic object. A surface patch model based on the topology of a user-specified reference mesh is employed to track the surface of the object over time. Multi-view 3D matching of surface patches using a novel cooperative minimisation approach provides initial motion estimates which are robust to large, rapid non-rigid changes of shape. A Laplacian deformation subsequently regularises the motion of the whole mesh using the weighted vertex displacements as soft constraints. An unregistered surface geometry independently reconstructed at each frame is incorporated as a shape prior to improve the quality of tracking. The method is evaluated in a challenging scenario of facial performance capture. Results demonstrate accurate tracking of fast, complex expressions over long sequences without use of markers or a pattern. © 2011 IEEE

Cooperative patch-based 3D surface tracking

This paper presents a novel dense motion capture technique which creates a temporally consistent mesh sequence from several calibrated and synchronised video sequences of a dynamic object. A surface patch model based on the topology of a user-specified reference mesh is employed to track the surface of the object over time. Multi-view 3D matching of surface patches using a novel cooperative minimisation approach provides initial motion estimates which are robust to large, rapid non-rigid changes of shape. A Laplacian deformation subsequently regularises the motion of the whole mesh using the weighted vertex displacements as soft constraints. An unregistered surface geometry independently reconstructed at each frame is incorporated as a shape prior to improve the quality of tracking. The method is evaluated in a challenging scenario of facial performance capture. Results demonstrate accurate tracking of fast, complex expressions over long sequences without use of markers or a pattern. © 2011 IEEE