Iterative filtering of SIFT keypoint matches for multi-view registration in Distributed Video Coding

Abstract

Multi-view registration is an essential step in order to generate the side information for multi-view Distributed Video Coding. As stated in our previous work (Ciobanu and Corte-Real, Multimed Tools Appl 48(3):411---436, 2010) it can be achieved by SIFT (scale-invariant feature transform) generated keypoint matches. The registration accuracy is vital for the adequate generation of side information and it directly depends on the reliable match of possibly all the available point to point correlations between two complete-overlapped views. We propose a solution to this problem based on iterative filtering of SIFT-generated keypoint matches, using the Hough transform and block matching. It aims the generic, real-life and constraint-free scenarios having an arbitrarily close angle between the two views. Practical results show an overall significant reduction of the outliers while maintaining a high rate of correct matches.