Citation:
Ruiz-Alzola J, Kikinis R, Westin C-F. Detection of Point Landmarks in Multidimensional Tensor Data. Signal Processing. 2001;81 (10) :2243-47.
Date Published:
2001 OctAbstract:
This paper describes a unified approach to the detection of point landmarks-whose neighborhoods convey discriminant information-including multidimensional scalar, vector, and higher-order tensor data. The method is based on the interpretation of generalized correlation matrices derived from the gradient of tensor functions, a probabilistic interpretation of point landmarks, and the application of tensor algebra. Results on both synthetic and real tensor data are presented.