Data fusion and multicue data matching by diffusion maps.

Stéphane Lafon; Yosi Keller; Ronald R Coifman

doi:10.1109/tpami.2006.223

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Data fusion and multicue data matching by diffusion maps.

Stéphane Lafon·Yosi Keller·Ronald R Coifman

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Abstract

Data fusion and multicue data matching are fundamental tasks of high-dimensional data analysis. In this paper, we apply the recently introduced diffusion framework to address these tasks. Our contribution is three-fold: First, we present the Laplace-Beltrami approach for computing density invariant embeddings which are essential for integrating different sources of data. Second, we describe a refinement of the Nyström extension algorithm called "geometric harmonics." We also explain how to use this tool for data assimilation. Finally, we introduce a multicue data matching scheme based on nonlinear spectral graphs alignment. The effectiveness of the presented schemes is validated by applying it to the problems of lipreading and image sequence alignment.

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Stéphane Lafon, Yosi Keller, Ronald R Coifman. 2006. Data fusion and multicue data matching by diffusion maps.. https://doi.org/10.1109/tpami.2006.223

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