185 research outputs found

    Multiple View Image Rectification

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    International audienceThis paper presents an extension of image rectification methods for an arbitrary number of views with aligned camera center. This technique can be used for stereoscopic rendering to enhance the perception comfort or for depth from stereo. In this paper, we first expose that epipolar geometry is not suited to solve this problem. Then we propose a non linear method that includes all the images in the rectification process. Our method only requires point correspondences between the views and can handle images with different resolutions. The tests show that the method is robust to noise and and to sparse point correspondences among the view

    Euclidean reconstruction of natural underwater scenes using optic imagery sequence

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    The development of maritime applications require monitoring, studying and preserving of detailed and close observation on the underwater seafloor and objects. Stereo vision offers advanced technologies to build 3D models from 2D still overlapping images in a relatively inexpensive way. However, while image stereo matching is a necessary step in 3D reconstruction procedure, even the most robust dense matching techniques are not guaranteed to work for underwater images due to the challenging aquatic environment. In this thesis, in addition to a detailed introduction and research on the key components of building 3D models from optic images, a robust modified quasi-dense matching algorithm based on correspondence propagation and adaptive least square matching for underwater images is proposed and applied to some typical underwater image datasets. The experiments demonstrate the robustness and good performance of the proposed matching approach

    DFR: Depth from Rotation by Uncalibrated Image Rectification with Latitudinal Motion Assumption

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    Despite the increasing prevalence of rotating-style capture (e.g., surveillance cameras), conventional stereo rectification techniques frequently fail due to the rotation-dominant motion and small baseline between views. In this paper, we tackle the challenge of performing stereo rectification for uncalibrated rotating cameras. To that end, we propose Depth-from-Rotation (DfR), a novel image rectification solution that analytically rectifies two images with two-point correspondences and serves for further depth estimation. Specifically, we model the motion of a rotating camera as the camera rotates on a sphere with fixed latitude. The camera's optical axis lies perpendicular to the sphere's surface. We call this latitudinal motion assumption. Then we derive a 2-point analytical solver from directly computing the rectified transformations on the two images. We also present a self-adaptive strategy to reduce the geometric distortion after rectification. Extensive synthetic and real data experiments demonstrate that the proposed method outperforms existing works in effectiveness and efficiency by a significant margin

    Uncalibrated stereo vision applied to breast cancer treatment aesthetic assessment

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    Mestrado Integrado. Engenharia Informática e Computação. Universidade do Porto. Faculdade de Engenharia. 201

    3D reconstruction of particle agglomerates using multiple scanning electron microscope stereo-pair images

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    Scanning electron microscopes (SEM) allow a detailed surface analysis of a wide variety of specimen. However, SEM image data does not provide depth information about a captured scene. This limitation can be overcome by recovering the hidden third dimension of the acquired SEM micrographs, for instance to fully characterize a particle agglomerate's morphology. In this paper, we present a method that allows the three-dimensional (3D) reconstruction of investigated particle agglomerates using an uncalibrated stereo vision approach that is applied to multiple stereo-pair images. The reconstruction scheme starts with a feature detection and subsequent matching in each pair of stereo images. Based on these correspondences, a robust estimate of the epipolar geometry is determined. A following rectification allows a reduction of the dense correspondence problem to a one-dimensional search along conjugate epipolar lines. So the disparity maps can be obtained using a dense stereo matching algorithm. To remove outliers while preserving edges and individual structures, a disparity refinement is executed using suitable image filtering techniques. The investigated specimen's qualitative depth's information can be directly calculated from the determined disparity maps. In a final step the resulting point clouds are registered. State-of-the-art algorithms for 3D reconstruction of SEM micrographs mainly focus on structures whose image pairs contain hardly or even none-occluded areas. The acquisition of multiple stereo-pair images from different perspectives makes it possible to combine the obtained point clouds in order to overcome occurring occlusions. The presented approach thereby enables the 3D illustration of the investigated particle agglomerates. © 2018 SPIE

    Calibration and Sensitivity Analysis of a Stereo Vision-Based Driver Assistance System

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    Az http://intechweb.org/ alatti "Books" fül alatt kell rákeresni a "Stereo Vision" címre és az 1. fejezetre
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