【文件属性】：
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