Efficient, robust, and fast global motion estimation for video coding

Abstract

In this paper, we propose an efficient, robust, and fast method for the estimation of global motion from image sequences. The method is generic in that it can accommodate various global motion models, from a simple translation to an eight-parameter perspective model. The algorithm is hierarchical and consists of three stages. In the first stage, a low-pass image pyramid is built. Then, an initial translation is estimated with full-pixel precision at the top of the pyramid using a modified n-step search matching. In the third stage, a gradient descent is executed at each level of the pyramid starting from the initial translation at the coarsest level. Due to the coarse initial estimation and the hierarchical implementation, the method is very fast. To increase robustness to outliers, we replace the usual formulation based on a quadratic error criterion with a truncated quadratic function. We have applied the algorithm to various test sequences within an MPEG-4 coding system. From the experimental results we conclude that global motion estimation provides significant performance gains for video material with camera zoom and/or pan. The gains result from a reduced prediction error and a more compact representation of motion. We also conclude that the robust error criterion can introduce additional performance gains without increasing computational complexity.

An Emphasizing Approach based on Enhanced Intuitionistic Fuzzy Logic Segmentation on Objects in Video Sequences

“…Thus, the first step in the algorithm is to compensate the motion of the camera. The global motion is modeled by an eight-parameter perspective motion model and estimated using a robust gradient-based technique [2]. An initial spatial partition of the current frame is obtained by applying the watershed segmentation algorithm.…”

Global Motion Estimation and Its Applications

“…Then, the estimated global motion parameters at the coarsest level are projected to its next high resolution level to get the refined global motion parameters. Finally, the refined global motion parameters are iteratively updated using a least-square based approach and the process continues until convergence [1]. Fig.…”

“…GMC/LMC based motion compensation mode selection approach in MPEG-4 is given [1], [2]. Global motion estimation and compensation is used in MPEG-4 advanced simple profiles (ASP) to remove the residual information of global motion.…”

Digital Video Transcoding

“…The estimation is referred to as global motion estimation (GME). Direct GME methods operate in the pixel-domain [61], [62]. They are computationally expensive due to the iterative processes in the nonlinear esti-mations and the number of pixels involved when the general perspective model is used.…”