Several algorithms for global motion estimation in video sequences using pixel-or block-based approaches have been published. Most known pixel-based methods lack in performance while when using block-based algorithms working on motion vectors, robustness to outliers and accuracy is missing. In this paper we present the fundamentals of a significantly improved, robust block-based method for global motion estimation in compressed domain following the generic Helmholtz principle. To this aim, we use motion vector fields as provided by MPEG data streams. Background PSNR values for four motion compensated test sequences show that our new method delivers results comparable to more complex algorithms.
Global motion is estimated either in the pixel domain or in block based domain. Until now, all the approaches regarding the latter are based on fixed sized blocks while the recent compression methods tend to use variable block sizes during motion estimation. In this paper we present a new procedure for global motion estimation based on a variable block size motion vector field. A block matching algorithm which is able to adapt the block size according to the motion complexity within the frame is used. The resulting motion vectors are employed for global motion estimation. Furthermore, binary foreground-background masks are created based on the frame-by-frame motion compensated differences by exploiting spatial conditions through anisotropic diffusion filtering. For global motion estimation the performance evaluation in terms of background PSNR shows an enhancement of more than 2.5 dB in the well-known ldquoStefanrdquo sequence, compared to the conventional case of fixed block size, at a reasonable implementation complexity
Motion compensated prediction (MCP) in hybrid video coding estimates a translational motion vector for a given block which is then used for residual computation. However, when complex motion like zoom, rotation, and perspective transformation occur, the translational model assumption does not always hold. This may result in higher residual energy and splitting of blocks, respectively. This paper proposes a skip mode based on higher-order parametric motion models. Often, these models provide a better prediction quality resulting in lower residual energy and larger block sizes. The proposed technique estimates a higher-order motion model between two given pictures. The encoder decides in terms of ratedistortion optimization whether to use the new skip mode for a block and therefore not to transfer any additional information like coefficient data. Experimental evaluation shows that the proposed technique can improve the coding performance of next generation video coding standards significantly.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.