Several techniques have been developed for recovering reflectance properties of real surfaces under unknown illumination conditions. However, in most cases, those techniques assume that the light sources are located at infinity, which cannot be applied to, for example, photometric modeling of indoor environments. In this paper, we propose two methods to estimate the surface reflectance property of an object, as well as the position of a light source from a single image without the distant illumination assumption. Given a color image of an object with specular reflection as an input, the first method estimates the light source position by fitting to the Lambertian diffuse component, while separating the specular and diffuse components by using an iterative relaxation scheme. Moreover, we extend the above method by using a single specular image as an input, thus removing its constraints on the diffuse reflectance property and the number of light sources. This method simultaneously recovers the reflectance properties and the light source positions by optimizing the linearity of a log-transformed Torrance-Sparrow model. By estimating the object's reflectance property and the light source position, we can freely generate synthetic images of the target object under arbitrary source directions and source-surface distances.
|出版ステータス||出版済み - 2003|
|イベント||Proceedings: Ninth IEEE International Conference on Computer Vision - Nice, フランス|
継続期間: 10 13 2003 → 10 16 2003
|その他||Proceedings: Ninth IEEE International Conference on Computer Vision|
|Period||10/13/03 → 10/16/03|
All Science Journal Classification (ASJC) codes
- コンピュータ ビジョンおよびパターン認識