Optical Flow-Based Fast Motion Parameters Estimation for Affine Motion Compensation

Adaptive search area for fast motion estimation

In this paper a new method for determining the search area for motion estimation algorithm based on block matching is suggested. In the proposed method the search area is adaptively found for each block of a frame. This search area is similar to that of the full search (FS) algorithm but smaller for most blocks of a frame. Therefore, the proposed algorithm is analogous to FS in terms of reg...

Model Parameters Estimation for Image Motion Compensation

Fast and optimal motion estimation method is proposed for electronic image stabilization. First, an approach for macro-block judgment is presented. Before motion vectors calculation, gradient information is analyzed, only useful reference blocks that are indispensable for accurate motion estimation are selected, by which the number of macro-blocks for subsequent calculation is reduced. Second, ...

Affine Transform Motion Compensation

Fast Piecewise-Affine Motion Estimation Without Segmentation

Current algorithmic approaches for piecewise affine motion estimation are based on alternating motion segmentation and estimation. We propose a new method to estimate piecewise affine motion fields directly without intermediate segmentation. To this end, we reformulate the problem by imposing piecewise constancy of the parameter field, and derive a specific proximal splitting optimization schem...

Motion Parameter Estimation from Optical Flow without Nuisance Parameters

Many kinds of computer vision problems can be formalized as statistical estimation problems with nuisance parameters. In the past, such problems have been solved without making any distinction between the nuisance parameters and structural ones. However, a theory of statistics suggests that eliminating the nuisance parameters by assuming a probability distribution on them improves estimation ac...