文件名称：An Efficient Exact-PGA Algorithm for Constant Curvature Manifolds
文件大小：352KB
文件格式：PDF
更新时间：2021-05-04 13:54:30
PGA
Manifold-valued datasets are widely encountered in many computer vision tasks. A non-linear analog of the PCA algorithm, called the Principal Geodesic Analysis (PGA) algorithm suited for data lying on Riemannian manifolds was reported in literature a decade ago. Since the objective function in the PGA algorithm is highly non-linear and hard to solve efficiently in general, researchers have proposed a linear approximation. Though this linear approximation is easy to compute, it lacks accuracy especially when the data exhibits a large variance