Landmarks inside the shape: Shape matching using image descriptors

In the last few decades, significant advances in image matching are provided by rich local descriptors that are defined through physical measurements such as reflectance. As such measurements are not naturally available for silhouettes, existing arsenal of image matching tools cannot be utilized in shape matching. We propose that the recently presented SPEM representation can be used analogous to image intensities to detect local keypoints using invariant image salient point detectors. We devise a shape similarity measure based on the number of matching internal regions. The performance of the similarity measure in planar shape retrieval indicates that the landmarks inside the shape silhouettes provide a strong representation of the regional characteristics of 2D planar shapes.