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Conference Papers Year : 2002

Kernel Temporal Component Analysis (KTCA)

Dominique Martinez
Alistair Bray
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We describe an efficient algorithm for simultaneously extracting multiple smoothly-varying non-linear invariances from time-series data. The method exploits the concept of maximising temporal predictability introduced by Stone in the linear domain - we term this temporal component analysis (TCA). Our current work extends this linear method into the non-linear domain using kernel-based methods; it performs a non-linear projection of the input into an unknown high-dimensional feature space, computing a linear solution in this space. In this paper we describe the improved on-line version of this algorithm (KTCA) for working on very large data sets, and demonstrate its applicability for computer vision by extracting non-linear disparity directly from grey-level stereo pairs, without pre-processing.
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Dates and versions

inria-00100795 , version 1 (26-09-2006)


  • HAL Id : inria-00100795 , version 1


Dominique Martinez, Alistair Bray. Kernel Temporal Component Analysis (KTCA). European Symposium on Artificial Neural Networks - ESANN'2002, Apr 2002, Bruges, Belgium, pp.477-482. ⟨inria-00100795⟩
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