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We present an approach for robust shape retrieval from databases containing articulated 3D models. Each shape is represented by the eigenvectors of an appropriately defined affinity matrix, forming a spectral embedding which achieves normalization against rigid-body transformations, uniform scaling, and shape articulation (i.e., bending). Retrieval is(More)
Communicated by (xxxxxxxxxx) We present an algorithm for finding a meaningful vertex-to-vertex correspondence between two triangle meshes, which is designed to handle general non-rigid transformations. Our algorithm operates on embeddings of the two shapes in the spectral domain so as to normalize them with respect to uniform scaling and rigid-body(More)
In this paper, we apply Nyström method, a sub-sampling and reconstruction technique, to speed up spectral mesh processing. We first relate this method to Kernel Principal Component Analysis (KPCA). This enables us to derive a novel measure in the form of a matrix trace, based soly on sampled data, to quantify the quality of Nyström approximation. The(More)
—Detecting the presence of licensed users and avoiding interference to them is vital to the proper operation of a Cognitive Radio (CR) network. Operating in a wideband channel requires high Nyquist sampling rates, which is limited by the state-of-the-art A/D converters. Compressive sampling is a promising solution to reduce sampling rates required in modern(More)
To make decisions about the long-term preservation and access of large digital collections, archivists gather information such as the collections' contents, their organizational structure, and their file format composition. To date, the process of analyzing a collection — from data gathering to exploratory analysis and final conclusions — has largely been(More)