Structure from motion estimation using a nonlinear Kalman filter

Venter, Chris (Christian Johannes) (2002-12)

Thesis (MScEng)--University of Stellenbosch, 2002.

Thesis

ENGLISH ABSTRACT: Structure from Motion is defined as the problem of extracting the 3d motion of a camera moving through a scene, as well as the 3d structure of the scene, from the image sequence produced by the camera over time. Several methods based on the Kalman filter have been proposed in the past, mostly based on the Extended Kalman filter. We propose an algorithm based on the dual Unscented Kalman filter to estimate the structure and motion of an object under perspective projection. It is shown that the algorithm is stable and accurate under synthetic as well as real-world conditions.

AFRIKAANSE OPSOMMING: Struktuur vanuit Beweging is 'n rekenaar-visie probleem waarin die 3d beweging van 'n kamera deur 'n ruimte, asook die 3d struktuur van die ruimte, bepaal moet word slegs vanuit die 2d beelde in die beeldreeks wat deur die kamera geneem word. 'n Verskeie reeks oplossings, gebaseer op die Kalman filter, is reeds voorgestelom die probleem op te los. Meeste van die oplossings implementeer die "Extended Kalman filter", of EKF. Ons stel 'n algoritme voor, gebaseer op 'n nuwe nie-lineêre benadering tot die Kalman filter, die sogenaamde "Unscented Kalman filter", of UKF. Hierdie algoritme bepaal die struktuur en beweging onder 'n perspektief-projeksie kamera. Daar word getoon dat die algoritme stabiel en akkuraat funskioneer onder sintetiese sowel as reële toevoer.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/53071
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