2008 Congress on Image and Signal Processing 2008
DOI: 10.1109/cisp.2008.621
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Close-Form Solution of Absolute Orientation Based on Inverse Problem of Orthogonal Matrices

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Cited by 7 publications
(4 citation statements)
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“…The next step was to use control points' coordinates in the GPS frame, the control points' coordinates in the world frame, and boundary coordinates in the world frame to calculate boundary points' coordinates in the GPS frame. This is the classic iterative closest point (ICP) problem [23]:…”
Section: B Gps Coordinate Transformation Basedmentioning
confidence: 99%
“…The next step was to use control points' coordinates in the GPS frame, the control points' coordinates in the world frame, and boundary coordinates in the world frame to calculate boundary points' coordinates in the GPS frame. This is the classic iterative closest point (ICP) problem [23]:…”
Section: B Gps Coordinate Transformation Basedmentioning
confidence: 99%
“…Bu nedenle mutlak yöneltme problemi için doğrudan (yani iteratif olmayan) bir çözüm geliştirmek yararlı bir çalışma olacaktır. Literatürde bilinen bazı doğrudan (direct) yöntemler arasında; doğrudan birim kuaterniyon çözümü, matris kare-kök çözümü, tekil değer ayrışımı (SVD)'na dayalı doğrudan çözüm ve doğrusal alt uzay yöntemine bağlı kapalı-form çözümü sayılabilir [11][12][13][14][15]. Bilgisayarlı görü araştırmalarında mutlak yöneltme, minimum nesne bilgisini kullanarak poz kestirimi (pose estimation) problemine doğrudan çözümler getirmeyi amaçlamaktadır.…”
Section: Introductionunclassified
“…By establishing the correspondence between views, the scale information can be estimated quickly, and then the depth recovery and the reconstruction and pose estimation of the target can be realized in the Euclidean space. In reference [8], the three-dimensional coordinates of the moving object are obtained by two cameras that measure the spatial constraints of the same spatial point between different image planes. After the 3D a reconstruction of single acquisition, the absolute orientation of the two acquisition point clouds is solved to achieve the target pose estimation and point cloud fusion.…”
Section: Introductionmentioning
confidence: 99%