%0 Journal Article %J IEEE Transactions on Pattern Analysis and Machine Intelligence %D 2006 %T A 3D shape constraint on video %A Hui Ji %A Fermüller, Cornelia %K 3D motion estimation %K algorithms %K Artificial intelligence %K CAMERAS %K decoupling translation from rotation %K Estimation error %K Fluid flow measurement %K Image Enhancement %K Image Interpretation, Computer-Assisted %K Image reconstruction %K Imaging, Three-Dimensional %K Information Storage and Retrieval %K integration of motion fields %K Layout %K minimisation %K Minimization methods %K Motion estimation %K multiple motion fields %K parameter estimation %K Pattern Recognition, Automated %K Photography %K practical constrained minimization %K SHAPE %K shape and rotation. %K shape vectors %K stability %K structure estimation %K surface normals %K Three-dimensional motion estimation %K video 3D shape constraint %K Video Recording %K video signal processing %X We propose to combine the information from multiple motion fields by enforcing a constraint on the surface normals (3D shape) of the scene in view. The fact that the shape vectors in the different views are related only by rotation can be formulated as a rank = 3 constraint. This constraint is implemented in an algorithm which solves 3D motion and structure estimation as a practical constrained minimization. Experiments demonstrate its usefulness as a tool in structure from motion providing very accurate estimates of 3D motion. %B IEEE Transactions on Pattern Analysis and Machine Intelligence %V 28 %P 1018 - 1023 %8 2006/06// %@ 0162-8828 %G eng %N 6 %R 10.1109/TPAMI.2006.109