Dominant motion estimation and video partitioning with a 1D signal approach

This paper presents a novel approach for an automatic partitioning of video sequences based on scene change detection and global motion estimation. The method is based on a 1D representation of images, the Bin transform, which is a discrete version of the Radon transform. Analysis of the motion and detection of the scene change are realized in the transform domain using online statistical techniques. The analysis of a 1D signal rather than the mostly used 2D image signal limits computational complexity by itself and permits fast algorithms.