Browsing by Author "Genc, Yacup"

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    Fast and accurate algorithms for projective multi-image structure from motion
    (2001-02) Oliensis, John; Genc, Yacup
    We describe algorithms for computing projective structure and motion from a multi-image sequence of tracked points. The algorithms are essentially linear, work for any motion of moderate size, and give accuracies similar to those of a maximum-likelihood estimate. They give better results than the Sturm/Triggs factorization approach and are equally fast, and they are much faster than bundle adjustment. Our experiments show that the (iterated) Sturm/Triggs approach often fails for linear camera motions. In adition, we study experimentally the common situation where the calibration is fixed and approximately known, comparing the projective versions of our algorithms to mixed projective/Euclidean strategies. We clarify the nature of dominant-plane compensation, showing that it can be considered a small-translation approximation rather than an approximation that the scene is planar. We show that projective algorithms accurately recover the (projected inverse depths and homographies despite the possibility of transforming the structure and motion by a projective transformation.
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    Three algorithms for 2-image and 2-image structure from motion
    (2001-02) Oliensis, John; Genc, Yacup
    We describe three approaches to 2-image and 2-image structure from motion. First, we present a new approximation to the least-squares image-reprojection error for 2 images. It depends only on the motion unknowns and is much more accurate than previous approximations such as the (weighted) coplanarity, especially for forward camera motions. We use this error to compute tight, rigorous upper and lower bounds on the true error and to study its properties experimentally. We demonstrate that the true error has many local minima for forward motions even when the motion is large. We propose and experimentally test a second approach, which is potentially more robust than bundle adjustment. Last, we describe algorithms for 2 images that reconstruct from the measured 2D affine deformations of image patches.