Riemannian Computing in Computer Vision

Riemannian analysis of closed curves and applications in medical imaging.- Human Activity analysis using manifold models of linear dynamical systems.- Pedestrian detection and tracking on tensor manifolds.- Face Recognition using subspaces and Grassmann manifold.- Domain Adaptation using parallel transports on Grassmann manifold.- Kernels on Riemannian Manifolds.- Sparse coding on manifolds and applications to diffusion tensor imaging.- Robust statistics on manifolds and applications to chromatic filtering.- Lighting insensitive face recognition.- Lie-algebraic averaging in Structure from motion problems.- Lie-algebraic methods for Robotic localization problems.- Clustering on Gauss maps for real-time interactive media.- Medical Shape Analysis.- Bayesian Shape Analysis in Images.- Tensor Data Analysis in Medical Imaging.- Trajectories on Manifolds for Activity Recognition.- Data approximation and summarization algorithms on manifolds