Video analysis via nonlinear dimensionality reduction

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Abstract

In this work we present an application of nonlinear dimensionality reduction techniques for video analysis. We review several methods for dimensionality reduction and then concentrate on the study of Diffusion Maps. First we show how diffusion maps can be applied to video analysis. For that end we study how to select the values of the parameters involved. This is crucial as a bad parameter selection produces misleading results. Using color histograms as features we present several results on how to use diffusion maps for video analysis.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition, Image Analysis and Applications - 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, Proceedings
Pages152-161
Number of pages10
StatePublished - 2007
Event12th Iberoamerican Congress on Pattern Recognition, CIARP 2007 - Vina del Mar-Valparaiso, Chile
Duration: 13 Nov 200716 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4756 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th Iberoamerican Congress on Pattern Recognition, CIARP 2007
Country/TerritoryChile
CityVina del Mar-Valparaiso
Period13/11/0716/11/07

Keywords

  • Dimensionality reduction
  • Video analysis

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