Reconstructing Shapes and Appearances of Thin Film Objects Using RGB Images

Yoshie Kobayashi, Tetsuro Morimoto, Imari Sato, Yasuhiro Mukaigawa, Takao Tomono, Katsushi Ikeuchi; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 3774-3782

Reconstruction of shapes and appearances of thin film objects can be applied to many fields such as industrial inspection, biological analysis, and archeology research. However, it comes with many challenging issues because the appearances of thin film can change dramatically depending on view and light directions. The appearance is deeply dependent on not only the shapes but also the optical parameters of thin film. In this paper, we propose a novel method to estimate shapes and film thickness. First, we narrow down candidates of zenith angle by degree of polarization and determine it by the intensity of thin film which increases monotonically along the zenith angle. Second, we determine azimuth angle from occluding boundaries. Finally, we estimate the film thickness by comparing a look-up table of color along the thickness and zenith angle with captured images. We experimentally evaluated the accuracy of estimated shapes and appearances and found that our proposed method is effective.