Human interaction to improve the image alignment on a cooperative robotic framework

On the one hand, it is usual that the current image registration techniques fail when images at hand have large differences due to dissimilarities on the point of views, occlusions, shadows and so on. On the other hand, humans are very good at finding correlations between salient points of images. We propose a method that acts when the automatic method fails, in this case, a human interacts on the computer vision system to help it to find a preliminary mapping between some salient points. Our method solves the alignment problem between two images in which a human (or oracle) imposes a partial correspondence between salient points extracted from the images through a Human-Machine Interface and the Interactive Alignment Estimation Method computes a new image alignment.