  In this paper, we present a spectral graph wavelet approach for shape
analysis of carpal bones of human wrist. We apply a metric called global
spectral graph wavelet signature for representation of cortical surface of the
carpal bone based on eigensystem of Laplace-Beltrami operator. Furthermore, we
propose a heuristic and efficient way of aggregating local descriptors of a
carpal bone surface to global descriptor. The resultant global descriptor is
not only isometric invariant, but also much more efficient and requires less
memory storage. We perform experiments on shape of the carpal bones of ten
women and ten men from a publicly-available database. Experimental results show
the excellency of the proposed GSGW compared to recent proposed GPS embedding
approach for comparing shapes of the carpal bones across populations.
