Two sample tests for mean 3D projective shapes from digital camera images

DOI10.1007/s11009-013-9363-6zbMath1307.62144OpenAlexW2074511136MaRDI QIDQ479163

Marius Buibas, Mingfei Qiu, Victor Patrangenaru

Publication date: 5 December 2014

Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11009-013-9363-6

zbMATH Keywords

quaternionsface recognitioncomputational statisticsFréchet means3D scene reconstruction from a pair of uncalibrated camera views3D~projective shapeasymptotic statistics on manifoldsextrinsic mean change on a Lie groupnonparametric bootstrap on manifoldsvisual quality control

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Directional data; spatial statistics (62H11) Image analysis in multivariate analysis (62H35)

Related Items (4)

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 ⋮ Extrinsic regression and anti-regression on projective shape manifolds

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonparametric two-sample tests on homogeneous Riemannian manifolds, Cholesky decompositions and diffusion tensor image analysis
• Random change on a Lie group and mean glaucomatous projective shape change detection from stereo pair images
• Statistical analysis on manifolds: a nonparametric approach for inference on shape spaces
• A nonparametric approach to 3D shape analysis from digital camera images. I.
• On the validity of the formal Edgeworth expansion
• Mean location and sample mean location on manifolds: Asymptotics, tests, confidence regions
• Large sample theory of intrinsic and extrinsic sample means on manifolds. I
• An invitation to 3-D vision. From images to geometric models.
• Nonparametric comparison of mean directions or mean axes
• The one- and multi-sample problem for functional data with application to projective shape analysis
• Large sample theory of intrinsic and extrinsic sample means on manifolds. II.
• Directions and projective shapes
• Improved Pivotal Methods for Constructing Confidence Regions With Directional Data
• 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
• Nonparametric Inference on Manifolds
• Bootstrap Test for Difference Between Means in Nonparametric Regression
• The bootstrap and Edgeworth expansion

This page was built for publication: Two sample tests for mean 3D projective shapes from digital camera images