Kernel Temporal Component Analysis (KTCA)

Dominique Martinez 1 Alistair Bray 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : 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.
Type de document :
Communication dans un congrès
European Symposium on Artificial Neural Networks - ESANN'2002, Apr 2002, Bruges, Belgium, pp.477-482, 2002
Liste complète des métadonnées

https://hal.inria.fr/inria-00100795
Contributeur : Publications Loria <>
Soumis le : mardi 26 septembre 2006 - 14:51:06
Dernière modification le : jeudi 11 janvier 2018 - 06:19:48

Identifiants

  • HAL Id : inria-00100795, version 1

Collections

Citation

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

Partager

Métriques

Consultations de la notice

127