Eigendecomposition of correlated images characterized by three parameters Saitwal, Kishor ; Maciejewski, Anthony A. ; Roberts, Rodney G. "This work was supported by the National Imagery and Mapping Agency under contract no. NMA201-00-1-1003 and through collaborative participation in the Robotics Consortium sponsored by the U. S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0012." Most eigendecomposition algorithms operate on correlated images that are characterized by only one parameter. Hence they lack the required specifications of fully general 3D image data sets, in which the images need to be characterized by three parameters. In this paper, an extension of one of the fastest known eigendecomposition algorithms is successfully implemented to improve the computational efficiency of computing the eigendecomposition of such 3D image sets. This algorithm can be used in pattern recognition applications such as fully general 3D pose estimation of objects. Colorado State University. Libraries 2006 text ; image application/pdf ECEaam00117.pdf FACFECEN100117ARTI eng c2006 IEEE
Eigendecomposition of correlated images characterized by three parameters
Saitwal, Kishor ; Maciejewski, Anthony A. ; Roberts, Rodney G.
"This work was supported by the National Imagery and Mapping Agency under contract no. NMA201-00-1-1003 and through collaborative participation in the Robotics Consortium sponsored by the U. S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0012."
Most eigendecomposition algorithms operate on correlated images that are characterized by only one parameter. Hence they lack the required specifications of fully general 3D image data sets, in which the images need to be characterized by three parameters. In this paper, an extension of one of the fastest known eigendecomposition algorithms is successfully implemented to improve the computational efficiency of computing the eigendecomposition of such 3D image sets. This algorithm can be used in pattern recognition applications such as fully general 3D pose estimation of objects.
Colorado State University. Libraries
2006
text ; image
application/pdf
ECEaam00117.pdf
FACFECEN100117ARTI
eng
c2006 IEEE