Titlebook: Riemannian Computing in Computer Vision; Pavan K. Turaga,Anuj Srivastava Book 2016 The Editor(s) (if applicable) and The Author(s), under

frozen-shoulder

Lie-Theoretic Multi-Robot Localization relative pose and orientation information can be provided, and it is scalable in that the computational complexity does not increase with the size of the robot team and increases linearly with the number of measurements taken from nearby robots. The proposed approach is validated with simulation in

Affable

Covariance Weighted Procrustes Analysisape and covariance structure is difficult due to the inherent non-identifiability. The method requires the specification of constraints to carry out inference, and we discuss some possible practical choices. We illustrate the methodology using data from fish silhouettes and mouse vertebra images.

MAOIS

Elastic Shape Analysis of Functions, Curves and Trajectoriests. A fundamental tool in shape analysis is the construction and implementation of geodesic paths between shapes. This is used to accomplish a variety of tasks, including the definition of a metric to compare shapes, the computation of intrinsic statistics for a set of shapes, and the definition of

枕墊

Elastic Shape Analysis of Surfaces and Imageshods by computing geodesic paths between highly articulated surfaces and shape statistics of manually generated surfaces. We also describe applications?of this framework to image registration and medical diagnosis.

generic

A General Least Squares Regression Framework on Matrix Manifolds for Computer Vision visual tracking, object categorization, and activity recognition to human interaction recognition. Our experiments reveal that the proposed method yields competitive performance, including state-of-the-art results on challenging activity recognition benchmarks.

深淵

in modeling camera motion), stick figures (e.g. for activity recognition), subspace comparisons (e.g. in face recognition), symmetric positive-definite matrices (e.g. in diffusion tensor imaging), and function-spaces (e.g. in studying shapes of closed contours).978-3-319-36095-9978-3-319-22957-7