Robust range image registration using local distribution of albedo

We propose a robust registration method for range images under a rough estimate of illumination. Because reflectance properties are invariant to changes in illumination, they are promising to range image registration of objects lacking in discriminative geometric features under variable illumination. In our method, we use adaptive regions to model the local distribution of reflectance, which enables us to stably extract reliable attributes of each point against illumination estimation. We use a level set method to grow robust and adaptive regions to define these attributes. A similarity metric between two attributes is defined using the principal component analysis to find matches. Moreover, remaining mismatches are efficiently removed using the rigidity constraint of surfaces. Our experiments using synthetic and real data demonstrate the robustness and effectiveness of our proposed method.