Range image recognition using invariant local features

Range image recognition gains importance in the recent years due to the developments in acquiring, displaying, and storing such data. In this paper, we present a novel method for matching range surfaces. Our method utilizes local surface properties and represents the geometry of local regions efficiently. Integrating the Scale Invariant Feature Transform (SIFT) with the shape index (SI) representation of the range images allows matching of surfaces with different scales and orientations. We apply the method for scaled, rotated, and occluded range images and demonstrate the effectiveness it by comparing the previous studies.