A nonparametric approach to 3D shape analysis from digital camera images. I.

DOI10.1016/j.jmva.2009.02.010zbMath1177.62059OpenAlexW2061646424MaRDI QIDQ1041060

J. Blot

Publication date: 27 November 2009

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2009.02.010

zbMATH Keywords

nonparametric bootstrap3D reconstructionconfidence regionsextrinsic meansasymptotic distributions on manifoldshigh level image analysispinhole camera imagesprojective shape

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Directional data; spatial statistics (62H11) Image analysis in multivariate analysis (62H35) Nonparametric statistical resampling methods (62G09) Computing methodologies for image processing (68U10)

Related Items (15)

Extrinsic Means and Antimeans ⋮ A nonparametric approach to 3D shape analysis from digital camera images – II ⋮ Projective shape analysis of contours and finite 3D configurations from digital camera images ⋮ Detecting statistical differences between average glaucoma indices of the eye recovered from virtual 3D reconstructions of the eye’s optic nerve head using 2D stereo images ⋮ A central limit theorem for extrinsic antimeans and estimation of Veronese-Whitney means and antimeans on planar Kendall shape spaces ⋮ Sticky central limit theorems on open books ⋮ Statistics on manifolds and landmarks based image analysis: a nonparametric theory with applications ⋮ Rejoinder to the discussion ⋮ Random change on a Lie group and mean glaucomatous projective shape change detection from stereo pair images ⋮ Two sample tests for mean 3D projective shapes from digital camera images ⋮ Differential Geometry for Model Independent Analysis of Images and Other Non-Euclidean Data: Recent Developments ⋮ Extrinsic regression and anti-regression on projective shape manifolds ⋮ Spherical Regression Models Using Projective Linear Transformations ⋮ Nonparametric analysis of non-Euclidean data on shapes and images ⋮ Challenges in topological object data analysis

Cites Work

• On the validity of the formal Edgeworth expansion
• Bootstrap methods: another look at the jackknife
• Large sample theory of intrinsic and extrinsic sample means on manifolds. I
• The one- and multi-sample problem for functional data with application to projective shape analysis
• Directions and projective shapes
• A distribution-free method of interval estimation for unsigned directional data
• Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh
• NEW LARGE SAMPLE AND BOOTSTRAP METHODS ON SHAPE SPACES IN HIGH LEVEL ANALYSIS OF NATURAL IMAGES
• Distributions of projective invariants and model-based machine vision
• Multiple View Geometry in Computer Vision
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