Low complexity dense motion estimation using phase correlation

Abstract

We propose a low-complexity dense motion estimation scheme particularly attractive for real-time video applications. Our scheme is based on overlapped block-based motion estimation using phase correlation at critical pixel locations. These form an irregularly sampled grid capturing salient motion features of a scene. The dense vector field is obtained by applying normalized convolution on the irregular grid. Our experiments show that our scheme provides reliable sub-pixel accuracy motion vectors corresponding to actual scene motion, outperforms differential and phase-based methods and yields comparable performance to more complex and time consuming robust motion estimation techniques.