VMV17

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https://diglib.eg.org/handle/10.2312/2631688

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Browsing VMV17 by Subject "Color"

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    Dense and Scalable Reconstruction from Unstructured Videos with Occlusions
    (The Eurographics Association, 2017) Wei, Jian; Resch, Benjamin; Lensch, Hendrik P. A.; Matthias Hullin and Reinhard Klein and Thomas Schultz and Angela Yao
    Depth-map-based multi-view stereo algorithms typically recover textureless surfaces by assuming smoothness per view, so they require processing different views to solve occlusions. Moreover, the highly redundant viewpoints of videos make exhaustive calculation of depth maps unfeasible for large scenes. This paper achieves dense and scalable reconstruction from videos by adaptively selecting a minimum subset of views from the unstructured camera paths, that are most beneficial for incremental occlusion handling and coverage improvement. Furthermore, we simplify and optimize each set of locally consistent points as the points accumulated from a cluster of previously processed views. By combining content-aware view selection and clustering, as well as cluster-wise point merging, our approach can reduce both computational and memory costs while producing accurate, concise, and dense 3D points, even for homogeneous areas. The superior efficiency and point-level fashion of our operations facilitate 3D modeling at large scales.
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    Visualization of Cardiac Blood Flow Using Anisotropic Ambient Occlusion for Lines
    (The Eurographics Association, 2017) Köhler, Benjamin; Grothoff, Matthias; Gutberlet, Matthias; Preim, Bernhard; Matthias Hullin and Reinhard Klein and Thomas Schultz and Angela Yao
    Ambient occlusion (AO) for lines (LineAO) was introduced by Eichelbaum et al. [EHS13] as an adaption of screen-space AO to static line bundles, such as white brain matter fiber tracts derived from diffusion tensor imaging (DTI). In this paper, we further adapt the LineAO technique to dynamic scenes, in particular the animation of blood flow-representing pathlines that were integrated in cardiac 4D phase-contrast magnetic resonance imaging (PC-MRI) data. 4D PC-MRI is a non-invasive technique that allows to acquire time-resolved blood flow velocity data in all three spatial dimensions, i.e., a 4D vector field of one heart beat. Our main extension is a line alignment factor that reduces the AO-induced darkening if nearby lines have similar screen-space tangents. We further enhance the perception of homogeneous flow by incorporating depth-dependent halos. Our technique facilitates the quicker identification of prominent flow structures while showing the full flow context.