1966
DOI: 10.1007/bf02289451
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A generalized solution of the orthogonal procrustes problem

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Cited by 1,673 publications
(860 citation statements)
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“…Then, we made use of orthogo-506 nal Procrustes rotation to rotate these dimensions towards an 507 interpretable solution as this is considered a powerful tech-508 nique for conducting hypothesis-guided rotation (McCrae 509 et al 1996). Through this technique, dimensions are rotated 510 to minimize the sum of squares of deviations from a 511 hypothesized target matrix (Schönemann 1966). The rota-512 tion thus involves a realignment of the position of the axes, 513 without changing their relative position.…”
mentioning
confidence: 99%
“…Then, we made use of orthogo-506 nal Procrustes rotation to rotate these dimensions towards an 507 interpretable solution as this is considered a powerful tech-508 nique for conducting hypothesis-guided rotation (McCrae 509 et al 1996). Through this technique, dimensions are rotated 510 to minimize the sum of squares of deviations from a 511 hypothesized target matrix (Schönemann 1966). The rota-512 tion thus involves a realignment of the position of the axes, 513 without changing their relative position.…”
mentioning
confidence: 99%
“…For instance, the nearest orthogonal matrix plays a role in computer vision [6], and we revisit its solution in Section 3. More or less equivalent to this is the solution to the orthogonal Procrustes problem [11]. For these and other matrix nearness problems we refer to [5,8].…”
Section: The Distance To a Matrix Groupmentioning
confidence: 99%
“…This problem has not been addressed, and we ignore if an analytic solution exists to solve it. It can be viewed as a generalization of the orthogonal Procrustes problem [9,10,11,12], which usually deals with the registration of a single pattern. In our study, the shift-invariant case will be considered hereafter.…”
Section: The Organizationmentioning
confidence: 99%
“…Eggert et al [10] reviewed the main methods that give an analytical solution to this rigid 3D registration problem: singular value decomposition (SVD) [9,19], unit quaternions [20], orthonormal matrix [21], and dual quaternions [22]. In [11], Gower and Dijksterhuis reviewed multiple different Procrustes problems and many generalizations.…”
Section: Rigid 3d Registration or Orthogonal Procrustes Problemmentioning
confidence: 99%