Exemplar Based Filtering of 2.5D Meshes of Faces

Abstract

In this work, we present a content-aware filtering for 2.5D meshes of faces. We propose an exemplar-based filter that corrects each point of a given mesh through local model-exemplar neighborhood comparison. We take advantage of prior knowledge of the models (faces) to improve the comparison. We first detect facial feature points, and create the point correctors for regions of each feature, and only use the correspondent regions for correcting a point of the filtered mesh.