`%0 Conference Proceedings`

`%4 sid.inpe.br/sibgrapi@80/2006/08.16.16.56`

`%2 sid.inpe.br/sibgrapi@80/2006/08.16.16.56.47`

`%T Estimation of Multiple Orientations and Multiple Motions in Multi-Dimensional Signals`

`%D 2006`

`%A Stuke, Ingo,`

`%A Barth, Erhardt,`

`%A Mota, Cicero,`

`%@affiliation Institute for Signal Processing, University of Luebeck`

`%@affiliation Institute for Neuro- and Bioinformatics, University of L uebeck`

`%@affiliation Departamento de Matemática, Universidade Federal do Amazonas`

`%E Oliveira Neto, Manuel Menezes de,`

`%E Carceroni, Rodrigo Lima,`

`%B Brazilian Symposium on Computer Graphics and Image Processing, 19 (SIBGRAPI)`

`%C Manaus`

`%8 8-11 Oct. 2006`

`%I IEEE Computer Society`

`%J Los Alamitos`

`%S Proceedings`

`%K multiple orientations, multiple motions, transparency, occlusion.`

`%X Estimation of multiple orientations in multi-dimensional signals is a strong non-linear problem. A solution form this problem is presented in two steps. First, it is linearized by introducing the so-called "mixed orientations parameters" as an unique, albeit implicit, descriptor of the orientations. Next, the non-linearities are solved in order to find the individual orientations. For two-dimensional signals, e.g., images, this decomposition step is solved by seeking for the roots of polynomials. For multi-dimensional signals, the decomposition problem is reduced to a cascade of decompositions problems in two dimensional signals and solved. Therefore, a full solution for the estimation of any numbers of orientations in any dimension is achieved.`

`%@language en`

`%3 MotaC_EstimationOrientationMotion.pdf`