Advances on Pose Estimation and 3D Resconstruction of 2 and 3-View Scenes

Abstract : The study of cameras and images has been a prominent subject since the beginning of computer vision, one of the main focus being the pose estimation and 3D reconstruction. The goal of this thesis is to tackle and study some specific problems and methods of the structure-from-motion pipeline in order to provide improvements in accuracy, broad studies to comprehend the advantages and disadvantages of the state-of-the-art models and useful implementations made available to the public. More specifically, we center our attention to stereo pairs and triplets of images and discuss some of the methods and models able to provide pose estimation and 3D reconstruction of the scene.First, we address the depth estimation task for stereo pairs using block-matching. This approach implicitly assumes that all pixels in the patch have the same depth producing the common artifact known as the ``foreground fattening effect''. In order to find a more appropriate support, Yoon and Kweon introduced the use of weights based on color similarity and spatial distance, analogous to those used in the bilateral filter. We present the theory of this method and the implementation we have developed with some improvements. We discuss some variants of the method and analyze its parameters and performance.Secondly, we consider the addition of a third view and study the trifocal tensor, which describes the geometric constraints linking the three views. We explore the advantages offered by this operator in the pose estimation task of a triplet of cameras as opposed to computing the relative poses pair by pair using the fundamental matrix. In addition, we present a study and implementation of several parameterizations of the tensor. We show that the initial improvement in accuracy of the trifocal tensor is not enough to have a remarkable impact on the pose estimation after bundle adjustment and that using the fundamental matrix with image triplets remains relevant.Finally, we propose using a different projection model than the pinhole camera for the pose estimation of perspective cameras. We present a method based on the matrix factorization due to Tomasi and Kanade that relies on the orthographic projection. This method can be used in configurations where other methods fail, in particular, when using cameras with long focal length lenses. The performance of our implementation of this method is compared to that given by the perspective-based methods, we consider that the accuracy achieved and its robustness make it worth considering in any SfM procedure
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Laura Fernandez Julia. Advances on Pose Estimation and 3D Resconstruction of 2 and 3-View Scenes. Signal and Image Processing. Université Paris-Est, 2018. English. ⟨NNT : 2018PESC1157⟩. ⟨tel-02125188⟩

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