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Graph based methods have been successfully used in computer vision for classification and matching. This is due to the fact that shapes can be conveniently represented using graph structures. In this paper we explore the use of a spectral invariant which is based on the wave kernel trace to characterize graphs. The wave kernel is the solution of wave equation defined using the Edge-based Laplacian...
Complex networks are finding increasing use in many scientific fields as a data representation. They are used to describe social networks, power grids, transportation networks, food webs and protein interactions in organisms, for example. A number of network models have been proposed to describe and explain the structure of these networks. In this paper we explore the problem of determining how well...
This paper presents a novel analysis and application of the eigensystem of the edge-based Laplacian of a graph. The advantage of using the edge-based Lapla-cian over its vertex-based counterpart is that it significantly expands the set of differential operators that can be implemented in the graph domain. We use the analysis to develop a novel method for defining poseinvariant signatures for non-rigid...
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