Design and Implementation of Efficient Video Stabilization Engine Using Maximum a Posteriori Estimation and Motion Energy Smoothing Approach

Abstract

To smooth the video content caused by handheld devices, this paper designs a hardware-oriented engine for efficient video stabilization. This engine is realized based on the motion energy computation. Maximum a posteriori estimation derives the global motion. Significantly, the motion energy smoothing accomplishes video stabilization. The global motion is smoothed by calculating the continuous and curve energy of successive frames. In addition, to achieve real-time video stabilization, efficient hardware architecture is proposed. The novel data reuse scheme is designed for enhancing the speed of corner point detection. The estimation skip technique is manipulated for lowering the computation of local motion estimation. Double buffering and pipeline running is designed for efficiently deriving the global motion. With these approaches, the corresponding hardware architecture has the characteristics of high efficiency and high throughput. The experimental results show that the proposed video stabilization engine can produce well-smooth videos and have high precision. The proposed hardware architecture enhances the performance of video stabilization with real-time and large resolution-processing ability. The objective comparison also demonstrates our good performance on video stabilization.