Using video for recovering texture

Abstract

Existing approaches to characterizing image texture usually rely on computing a local response to a bank of correlation filters, such as derivatives of a Gaussian, in one image. Recently, significant progress has been made in characterizing a single texture under varying viewpoint and illumination conditions, leading to the bi-directional texture function that describes the smooth variation of filter responses as a function of viewpoint and illumination. However, this technique does not attempt to exploit the redundancy of multiple images; each image is treated independently. In video data, close correspondences between frames enable a new form of texture analysis that incorporates local 3D structure as well as intensity variation. We exploit this relationship to characterize texture with significant 3D structure, such as foliage, across a range of viewpoints. This paper presents a general overview of these ideas and preliminary results.