Spatially-Varying Image Warps for Scene Alignment

This paper proposes a method to align a set of images captured from multiple view points. Traditional methods using image warps parameterized by global transformations suffer from the problem of misalignment due to parallax effects induced by camera motions between images and depth variations of the scene. Our method parameterizes warps using mesh deformation and achieves spatially-varying transformations to alleviate the misalignment problem. The proposed method has two stages: a hybrid image alignment stage which combines direct-based methods and feature-based methods, followed by a shape-preserving aggregation stage which further refines the result. Experiments show that our method achieves better alignment and provides visually pleasing image summaries for scenes.