Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

Principal geodesic analysis

Known as: Geodesic (disambiguation), PGA 
In geometric data analysis and statistical shape analysis, principal geodesic analysis is a generalization of principal component analysis to a non… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2014
2014
In fields ranging from computer vision to signal processing and statistics, increasing computational power allows a move from… Expand
  • figure 2.1
  • figure 4.1
  • table 5.1
  • figure 5.1
  • table 5.2
Highly Cited
2013
Highly Cited
2013
Principal geodesic analysis (PGA) is a generalization of principal component analysis (PCA) for dimensionality reduction of data… Expand
  • table 1
  • figure 1
  • figure 2
2013
2013
In this paper, we consider the action recognition problem based on geometrical structure. Our method uses a low dimensional… Expand
  • figure 1
  • figure 3
  • figure 2
  • figure 4
  • figure 5
Highly Cited
2010
Highly Cited
2010
Manifolds are widely used to model non-linearity arising in a range of computer vision applications. This paper treats statistics… Expand
  • figure 1
  • table 1
  • figure 2
  • figure 3
  • figure 4
2007
2007
In this paper, we describe a weighted principal geodesic analysis (WPGA) method to extract features for gender classification… Expand
2007
2007
This paper describes how face recognition can be effected using 3D shape information extracted from single 2D image views. We… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
Highly Cited
2007
Highly Cited
2007
Abstract The aim in this paper is to use principal geodesic analysis to model the statistical variations for sets of facial… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Highly Cited
2004
Highly Cited
2004
Diffusion tensor magnetic resonance imaging (DT-MRI) is emerging as an important tool in medical image analysis of the brain… Expand
  • figure 1
  • figure 2
2004
2004
The use of statistical shape models in medical image analysis is growing due to the ability to incorporate prior organ shape… Expand
Highly Cited
2003
Highly Cited
2003
Principal component analysis has proven to be useful for understanding geometric variability in populations of parameterized… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4