In this paper, a method of a novel combination photometric stereo which can estimate surface normals precisely even for images including shadows and specular reflection is proposed. Assuming that the number of input images for photometric stereo is more than three, the proposed method can exclude pixels affected by shadows and specular reflection by analyzing distributions of albedos and normal vectors computed from Nc3 combinations for n input images. In these distributions, the proposed method define a novel value "compactness". The compactness indicates the degree of concentration of albedos and surface normals, which should be the same values if all pixel intensities of input images perfectly obey Lambcrtian model without any error. Finally pixels which are included in neither shadows nor specular reflection are chosen by voting using the compactness. The proposed method is experimentally verified that it can provide accurate surface normals in the presence of shadows and specular reflection and it is superior to with better accuracy than previous works. Moreover a small device have been developed which supplies eight images varying in light positions and can be attached to smartphones. A possibility of practical use of the proposed method with the device is also verified.
|ジャーナル||Seimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering|
|出版ステータス||Published - 2015|
ASJC Scopus subject areas
- Mechanical Engineering