Enhancing accuracy and sharpness of motion field with adaptive scheme and occlusion-aware filter

In this study, the authors propose an adaptive scheme to improve motion estimation of a variational model based on image features and flow quality measurements. Using image features, the authors introduce adaptive functions and inject them into the energy function to fine-tune the estimation process. They propose a hybrid scheme to deal with large motions and improve the accuracy of the flow field. They introduce a trusted-map based on constraints to measure flow quality. They use this map as a reference for the proposed occlusion-aware filter. The proposed filter and hybrid scheme are integrated to correct the flow field iteratively, thus significantly improving the estimation results. The filter also enhances the flow field in occlusion areas. The authors experimental results demonstrate that their method provides sharp flow fields and significantly improved estimation accuracy.