Statistical Shape Analysis by John Dryden

A concise, systematic treatment of methods for representing, modeling and making statistical inference about object shape using landmark and curve data; it develops the geometric foundations (Kendall shape spaces and Procrustes alignment), formulates probability models and hypothesis tests on nonlinear shape manifolds, and describes dimension-reduction, regression and deformation-based approaches alongside computational algorithms and applied examples from biology, medicine and image analysis.