Rendu basé image avec contraintes sur les gradients
This addresses a specific problem in computer vision for generating novel views from multi-view images, with incremental improvements over existing methods.
The paper tackles artifacts in multi-view image-based rendering caused by discontinuities in blending weights by imposing constraints on image gradients, resulting in a method that numerically outperforms state-of-the-art approaches and eliminates visibility-related artifacts.
Multi-view image-based rendering consists in generating a novel view of a scene from a set of source views. In general, this works by first doing a coarse 3D reconstruction of the scene, and then using this reconstruction to establish correspondences between source and target views, followed by blending the warped views to get the final image. Unfortunately, discontinuities in the blending weights, due to scene geometry or camera placement, result in artifacts in the target view. In this paper, we show how to avoid these artifacts by imposing additional constraints on the image gradients of the novel view. We propose a variational framework in which an energy functional is derived and optimized by iteratively solving a linear system. We demonstrate this method on several structured and unstructured multi-view datasets, and show that it numerically outperforms state-of-the-art methods, and eliminates artifacts that result from visibility discontinuities