18 research outputs found

    Image-based photo hulls for fast and photo-realistic new view synthesis

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    We present an efficient image-based rendering algorithm that generates views of a scene's photo hull. The photo hull is the largest 3D shape that is photo-consistent with photographs taken of the scene from multiple viewpoints. Our algorithm, image-based photo hulls (IBPH), like the image-based visual hulls (IBVH) algorithm from Matusik et al. on which it is based, takes advantage of epipolar geometry to efficiently reconstruct the geometry and visibility of a scene. Our IBPH algorithm differs from IBVH in that it utilizes the color information of the images to identify scene geometry. These additional color constraints result in more accurately reconstructed geometry, which often projects to better synthesized virtual views of the scene. We demonstrate our algorithm running in a realtime 3D telepresence application using video data acquired from multiple viewpoints

    Novel volumetric scene reconstruction methods for new view synthesis

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    Dissertation made openly available per email from author, 11/07/2016Ph.D.Russell M. Merserea

    Multi-resolution space carving using level set methods

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    We present a multi-resolution space carving algorithm that reconstructs a 3D model of visual scene photographed by a calibrated digital camera placed at multiple viewpoints. Our approach employs a level set framework for reconstructing the scene. Unlike most standard space carving approaches, our level set approach produces a smooth reconstruction composed of manifold surfaces. Our method outputs a polygonal model, instead of a collection of voxels. We texturemap the reconstructed geometry using the photographs, and then render the model to produce photo-realistic new views of the scene. 1

    Reconstructing Surfaces by Volumetric Regularization

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    We present a new method of surface reconstruction that generates smooth and seamless models from sparse, noisy, and non-uniform range data. Data acquisition techniques from computer vision, such as stereo range images and space carving, produce three dimensional point sets that are imprecise and non-uniform when compared to laser or optical range scanners. Traditional reconstruction algorithms designed for dense and precise data cannot be used on stereo range images and space carved volumes. Our method constructs a three dimensional implicit surface, formulated as a summation of weighted radial basis functions. We achieve three primary advantages over existing algorithms: (1) the implicit functions we construct estimate the surface well in regions where there is little data; (2) the reconstructed surface is insensitive to noise in data acquisition because we can allow the surface to approximate, rather than exactly interpolate, the data; and (3) the reconstructed surface is locally detailed, yet globally smooth, because we use radial basis functions that achieve multiple orders of smoothness
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