Efficient online real-time video stabilization with a novel least squares formulation and parallel AC-RANSAC.

ABSTRACT

A novel online real-time video stabilization algorithm (LSstab) that suppresses unwanted motion jitters based on cinematography principles is presented. LSstab features a parallel realization of the a-contrario RANSAC (AC-RANSAC) algorithm to estimate the inter-frame camera motion parameters. A novel least squares based smoothing cost function is then proposed to mitigate undesirable camera jitters according to cinematography principles. A recursive least square solver is derived to minimize the smoothing cost function with a linear computation complexity. LSstab is evaluated using a suite of publicly available videos against state-of-the-art video stabilization methods. Results show that LSstab achieves comparable or better performance, which attains real-time processing speed when a GPU is used.