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Titlebook: Advances in Visual Computing; 10th International S George Bebis,Richard Boyle,Mark Carlson Conference proceedings 2014 Springer Internation

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樓主: Consonant
31#
發(fā)表于 2025-3-26 21:36:46 | 只看該作者
3D Deformable Spatial Pyramid for Dense 3D Motion Flow of Deformable Objecte search and efficiently handles even large deformations with the pyramid graph model. As demonstrated in the experimental results, the proposed algorithm shows robustness in various deformation scenarios.
32#
發(fā)表于 2025-3-27 04:27:41 | 只看該作者
33#
發(fā)表于 2025-3-27 06:41:51 | 只看該作者
34#
發(fā)表于 2025-3-27 10:58:18 | 只看該作者
Statistical Estimation of Fluid Flow: An Image Restoration Approaches of spatial estimation of the auto-regressive STAR model and converts motion estimation into a restoration problem, where the local field can be computed fast in the frequency domain, while various natural constraints can be taken into account within the inversion strategy of the motion estimation process.
35#
發(fā)表于 2025-3-27 13:46:02 | 只看該作者
Image Classification via Semi-supervised Feature Extraction with Out-of-Sample Extensiones in order to study the performance of the proposed method. These experiments demonstrate much improvement over the state-of-the-art algorithms that are either based on label propagation or semi-supervised graph-based embedding.
36#
發(fā)表于 2025-3-27 20:27:16 | 只看該作者
0302-9743 4, held in Las Vegas, NV, USA. The 74 revised full papers and 55 poster papers presented together with 39 special track papers were carefully reviewed and selected from more than 280 submissions. The papers are organized in topical sections: Part I (LNCS 8887) comprises computational bioimaging, com
37#
發(fā)表于 2025-3-28 00:59:17 | 只看該作者
38#
發(fā)表于 2025-3-28 02:57:13 | 只看該作者
39#
發(fā)表于 2025-3-28 08:20:02 | 只看該作者
40#
發(fā)表于 2025-3-28 13:35:20 | 只看該作者
Voronoi Diagrams of Line Segments in 3D, with Application to Automatic Rigging with a presentation of an alternative method involving the specification of a system of linear equations. We show that our Voronoi diagram method can be used to create a Voronoi partitioning of an input model, and how such a segmentation process can be used for automatic rigging.
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