Optimal visual motion estimation: a note

The problem of estimating 3D motion in an optimal manner using correspondences of features in two views is analyzed. The importance of having an optimal estimator is twofold: first, for the estimation itself and, second, for the bound it offers on how much sensitivity one can expect from a two-frame, point-based motion algorithm. The optimal estimator turns out to be nonlinear, and for that reason, techniques that provide very good initial guesses for the iterative computation of the optimal estimator are developed     

Structure from motion using line correspondences

A theory is presented for the computation of three-dimensional motion and structure from dynamic imagery, using only line correspondences. The traditional approach of corresponding microfeatures (interesting points-highlights, corners, high-curvature points, etc.) is reviewed and its shortcomings are discussed. Then, a theory is presented that describes a closed form solution to the motion and structure determination problem from line correspondences in three views. The theory is compared with previous ones that are based on nonlinear equations and iterative methods.     

Optical Flow Estimation Using Discontinuity Conforming Filters

Discontinuities and large image displacements pose some of the hardest problems in flow estimation. This paper proposes a set of filters that change shape to avoid blending of the constraints across discontinuity boundaries according to an incompatibility measure of the constraints of neighboring pixels. The algorithm is embedded in a coarse to fine multigrid scheme to address the problem of large displacements. We report results on real and synthetic images which show that the algorithm works very well.     

Scene Reconstruction and Robot Navigation Using Dynamic Fields

In this paper, we present an approach to autonomous robot navigation in an unknown environment. We design and integrate algorithms to reconstruct the scene, locate obstacles and do short-term field-based path planning. The scene reconstruction is done using a region matching flow algorithm to recover image deformation and structure from motion to recover depth. Obstacles are located by comparing the surface normal of the known floor with the surface normal of the scene. Our path planning method is based on electric-like fields and uses current densities that can guarantee fields without local minima and maxima which can provide solutions without the need of heuristics that plague the more traditional potential fields approaches. We implemented a modular distributed software platform (FBN) to test this approach and we ran several experiments to verify the performance with very encouraging results.