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.
Using video for recovering texture
01.01.2001
1103853 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Using Video for Recovering Texture
British Library Conference Proceedings | 2001
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